{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime as dt\n",
    "from salishsea_tools import evaltools as et, viz_tools\n",
    "import os\n",
    "import datetime as dt\n",
    "import gsw\n",
    "import matplotlib.gridspec as gridspec\n",
    "import matplotlib as mpl\n",
    "import matplotlib.dates as mdates\n",
    "import cmocean as cmo\n",
    "import scipy.interpolate as sinterp\n",
    "import cmocean\n",
    "import json\n",
    "import f90nml\n",
    "from collections import OrderedDict\n",
    "from scipy.stats.mstats import gmean\n",
    "\n",
    "fs=16\n",
    "mpl.rc('xtick', labelsize=fs)\n",
    "mpl.rc('ytick', labelsize=fs)\n",
    "mpl.rc('legend', fontsize=fs)\n",
    "mpl.rc('axes', titlesize=fs)\n",
    "mpl.rc('axes', labelsize=fs)\n",
    "mpl.rc('figure', titlesize=fs)\n",
    "mpl.rc('font', size=fs)\n",
    "mpl.rc('font', family='sans-serif', weight='normal', style='normal')\n",
    "\n",
    "import warnings\n",
    "#warnings.filterwarnings('ignore')\n",
    "from IPython.display import Markdown, display\n",
    "\n",
    "%matplotlib inline\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import Puget Sound data and create dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_excel('/ocean/ksuchy/MOAD/observe/SSMSP_TransBoundary_Extract_2014-2019_Verticals_Keister_Lab.xlsx',engine='openpyxl',sheet_name='SSMSP 2014-2019 Density&Biomass')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>BugSampleID</th>\n",
       "      <th>Project</th>\n",
       "      <th>Sample Code</th>\n",
       "      <th>Sampling Group</th>\n",
       "      <th>Station</th>\n",
       "      <th>Site Name</th>\n",
       "      <th>Basin</th>\n",
       "      <th>Sub Basin</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>...</th>\n",
       "      <th>Ind Carbon (ug)</th>\n",
       "      <th>Density (#/m3)</th>\n",
       "      <th>Final Carbon (mg/m3)</th>\n",
       "      <th>Species Size Category Aggregation</th>\n",
       "      <th>Size Category Aggregation</th>\n",
       "      <th>Collection Confidence</th>\n",
       "      <th>Carbon Regression EQ</th>\n",
       "      <th>C to DW multipier</th>\n",
       "      <th>DW Regression Equation</th>\n",
       "      <th>C/DW Source</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>93945</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>060817HCB004V1454</td>\n",
       "      <td>HCSEG</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>...</td>\n",
       "      <td>122.333000</td>\n",
       "      <td>5.169013</td>\n",
       "      <td>3.185477</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>High</td>\n",
       "      <td>C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%</td>\n",
       "      <td>C = DW * 37%</td>\n",
       "      <td>DW(ug)=0.0049*([Length(mm)])^2.957)*1000</td>\n",
       "      <td>Ikeda &amp; Shiga, 1999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>93946</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>060817HCB004V1454</td>\n",
       "      <td>HCSEG</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>...</td>\n",
       "      <td>107.303200</td>\n",
       "      <td>0.068013</td>\n",
       "      <td>0.010533</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>High</td>\n",
       "      <td>C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%</td>\n",
       "      <td>C = DW * 37%</td>\n",
       "      <td>DW(ug)=0.0049*([Length(mm)])^2.957)*1000</td>\n",
       "      <td>Ikeda &amp; Shiga, 1999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>93962</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>060817HCB004V1454</td>\n",
       "      <td>HCSEG</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>...</td>\n",
       "      <td>17.764660</td>\n",
       "      <td>21.764267</td>\n",
       "      <td>0.397324</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>High</td>\n",
       "      <td>C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%</td>\n",
       "      <td>C = DW * 37%</td>\n",
       "      <td>DW(ug)=0.0049*([Length(mm)])^2.957)*1000</td>\n",
       "      <td>Ikeda &amp; Shiga, 1999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>94018</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>030917HCB003V1218</td>\n",
       "      <td>HCSEG</td>\n",
       "      <td>HCB003V</td>\n",
       "      <td>Eldon</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.53787</td>\n",
       "      <td>-123.0096</td>\n",
       "      <td>...</td>\n",
       "      <td>343.152100</td>\n",
       "      <td>1.730036</td>\n",
       "      <td>0.564992</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>High</td>\n",
       "      <td>C(ug)=((0.02 * [Length (mm)]^2.1)*1000)*37%</td>\n",
       "      <td>C = DW * 37%</td>\n",
       "      <td>DW(μg) = (0.02 * [Length(mm)]^2.1)*1000</td>\n",
       "      <td>Kafanov &amp; Fedotov, 1982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>94030</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>030917HCB003V1218</td>\n",
       "      <td>HCSEG</td>\n",
       "      <td>HCB003V</td>\n",
       "      <td>Eldon</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.53787</td>\n",
       "      <td>-123.0096</td>\n",
       "      <td>...</td>\n",
       "      <td>17.764660</td>\n",
       "      <td>0.812593</td>\n",
       "      <td>0.090677</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>High</td>\n",
       "      <td>C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%</td>\n",
       "      <td>C = DW * 37%</td>\n",
       "      <td>DW(ug)=0.0049*([Length(mm)])^2.957)*1000</td>\n",
       "      <td>Ikeda &amp; Shiga, 1999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81582</th>\n",
       "      <td>31509</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>050615MUKV1200</td>\n",
       "      <td>TUL</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>...</td>\n",
       "      <td>7.450710</td>\n",
       "      <td>98.804469</td>\n",
       "      <td>0.252324</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Keister Lab estimate, 2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81583</th>\n",
       "      <td>38434</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>081315MUKV1121</td>\n",
       "      <td>TUL</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>...</td>\n",
       "      <td>7.450710</td>\n",
       "      <td>8.634707</td>\n",
       "      <td>0.011568</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Keister Lab estimate, 2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81584</th>\n",
       "      <td>38675</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>082615MUKV1116</td>\n",
       "      <td>TUL</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>...</td>\n",
       "      <td>2.868051</td>\n",
       "      <td>27.045302</td>\n",
       "      <td>0.077567</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Keister Lab estimate, 2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81585</th>\n",
       "      <td>39535</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>050615CAMV1305</td>\n",
       "      <td>TUL</td>\n",
       "      <td>CAMV</td>\n",
       "      <td>Camano Head</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>48.05901</td>\n",
       "      <td>-122.3873</td>\n",
       "      <td>...</td>\n",
       "      <td>7.450710</td>\n",
       "      <td>43.628610</td>\n",
       "      <td>0.325064</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Moderate</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>C (ug) = 8.0935*[Length (mm)]-1.0883</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Keister Lab estimate, 2016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81586</th>\n",
       "      <td>104254</td>\n",
       "      <td>SSMSP</td>\n",
       "      <td>080318HCB004V1114</td>\n",
       "      <td>HCSEG</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>...</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>4.105091</td>\n",
       "      <td>0.004105</td>\n",
       "      <td>Unknown Nauplius</td>\n",
       "      <td>Unknown Nauplius</td>\n",
       "      <td>High</td>\n",
       "      <td>NONE</td>\n",
       "      <td>NONE</td>\n",
       "      <td>NONE</td>\n",
       "      <td>Keister Lab estimate, 2016</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81587 rows × 38 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       BugSampleID Project        Sample Code Sampling Group  Station  \\\n",
       "0            93945   SSMSP  060817HCB004V1454          HCSEG  HCB004V   \n",
       "1            93946   SSMSP  060817HCB004V1454          HCSEG  HCB004V   \n",
       "2            93962   SSMSP  060817HCB004V1454          HCSEG  HCB004V   \n",
       "3            94018   SSMSP  030917HCB003V1218          HCSEG  HCB003V   \n",
       "4            94030   SSMSP  030917HCB003V1218          HCSEG  HCB003V   \n",
       "...            ...     ...                ...            ...      ...   \n",
       "81582        31509   SSMSP     050615MUKV1200            TUL     MUKV   \n",
       "81583        38434   SSMSP     081315MUKV1121            TUL     MUKV   \n",
       "81584        38675   SSMSP     082615MUKV1116            TUL     MUKV   \n",
       "81585        39535   SSMSP     050615CAMV1305            TUL     CAMV   \n",
       "81586       104254   SSMSP  080318HCB004V1114          HCSEG  HCB004V   \n",
       "\n",
       "           Site Name          Basin        Sub Basin  Latitude  Longitude  \\\n",
       "0      Sisters Point     Hood Canal     S Hood Canal  47.35620  -123.0249   \n",
       "1      Sisters Point     Hood Canal     S Hood Canal  47.35620  -123.0249   \n",
       "2      Sisters Point     Hood Canal     S Hood Canal  47.35620  -123.0249   \n",
       "3              Eldon     Hood Canal     S Hood Canal  47.53787  -123.0096   \n",
       "4              Eldon     Hood Canal     S Hood Canal  47.53787  -123.0096   \n",
       "...              ...            ...              ...       ...        ...   \n",
       "81582       Mukilteo  Whidbey Basin  S Whidbey Basin  47.97166  -122.3222   \n",
       "81583       Mukilteo  Whidbey Basin  S Whidbey Basin  47.97166  -122.3222   \n",
       "81584       Mukilteo  Whidbey Basin  S Whidbey Basin  47.97166  -122.3222   \n",
       "81585    Camano Head  Whidbey Basin  S Whidbey Basin  48.05901  -122.3873   \n",
       "81586  Sisters Point     Hood Canal     S Hood Canal  47.35620  -123.0249   \n",
       "\n",
       "       ... Ind Carbon (ug) Density (#/m3)  Final Carbon (mg/m3)  \\\n",
       "0      ...      122.333000       5.169013              3.185477   \n",
       "1      ...      107.303200       0.068013              0.010533   \n",
       "2      ...       17.764660      21.764267              0.397324   \n",
       "3      ...      343.152100       1.730036              0.564992   \n",
       "4      ...       17.764660       0.812593              0.090677   \n",
       "...    ...             ...            ...                   ...   \n",
       "81582  ...        7.450710      98.804469              0.252324   \n",
       "81583  ...        7.450710       8.634707              0.011568   \n",
       "81584  ...        2.868051      27.045302              0.077567   \n",
       "81585  ...        7.450710      43.628610              0.325064   \n",
       "81586  ...        0.200000       4.105091              0.004105   \n",
       "\n",
       "      Species Size Category Aggregation Size Category Aggregation  \\\n",
       "0                              Amphipod                  Amphipod   \n",
       "1                              Amphipod                  Amphipod   \n",
       "2                              Amphipod                  Amphipod   \n",
       "3                              Amphipod                  Amphipod   \n",
       "4                              Amphipod                  Amphipod   \n",
       "...                                 ...                       ...   \n",
       "81582                       Unknown Egg               Unknown Egg   \n",
       "81583                       Unknown Egg               Unknown Egg   \n",
       "81584                       Unknown Egg               Unknown Egg   \n",
       "81585                       Unknown Egg               Unknown Egg   \n",
       "81586                  Unknown Nauplius          Unknown Nauplius   \n",
       "\n",
       "      Collection Confidence                           Carbon Regression EQ  \\\n",
       "0                      High  C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%   \n",
       "1                      High  C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%   \n",
       "2                      High  C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%   \n",
       "3                      High    C(ug)=((0.02 * [Length (mm)]^2.1)*1000)*37%   \n",
       "4                      High  C(ug)=(0.0049*([Length(mm)])^2.957)*1000)*37%   \n",
       "...                     ...                                            ...   \n",
       "81582              Moderate           C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81583              Moderate           C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81584              Moderate           C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81585              Moderate           C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81586                  High                                           NONE   \n",
       "\n",
       "                          C to DW multipier  \\\n",
       "0                              C = DW * 37%   \n",
       "1                              C = DW * 37%   \n",
       "2                              C = DW * 37%   \n",
       "3                              C = DW * 37%   \n",
       "4                              C = DW * 37%   \n",
       "...                                     ...   \n",
       "81582  C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81583  C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81584  C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81585  C (ug) = 8.0935*[Length (mm)]-1.0883   \n",
       "81586                                  NONE   \n",
       "\n",
       "                         DW Regression Equation                 C/DW Source  \n",
       "0      DW(ug)=0.0049*([Length(mm)])^2.957)*1000         Ikeda & Shiga, 1999  \n",
       "1      DW(ug)=0.0049*([Length(mm)])^2.957)*1000         Ikeda & Shiga, 1999  \n",
       "2      DW(ug)=0.0049*([Length(mm)])^2.957)*1000         Ikeda & Shiga, 1999  \n",
       "3       DW(μg) = (0.02 * [Length(mm)]^2.1)*1000     Kafanov & Fedotov, 1982  \n",
       "4      DW(ug)=0.0049*([Length(mm)])^2.957)*1000         Ikeda & Shiga, 1999  \n",
       "...                                         ...                         ...  \n",
       "81582                                      NONE  Keister Lab estimate, 2016  \n",
       "81583                                      NONE  Keister Lab estimate, 2016  \n",
       "81584                                      NONE  Keister Lab estimate, 2016  \n",
       "81585                                      NONE  Keister Lab estimate, 2016  \n",
       "81586                                      NONE  Keister Lab estimate, 2016  \n",
       "\n",
       "[81587 rows x 38 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['BugSampleID', 'Project', 'Sample Code', 'Sampling Group', 'Station',\n",
       "       'Site Name', 'Basin', 'Sub Basin', 'Latitude', 'Longitude',\n",
       "       'Date Category', 'Sample Date', 'Sample Year', 'Sample Month',\n",
       "       'Sample Time', 'Tow Type', 'Mesh Size', 'Diameter (cm)',\n",
       "       'Station Depth (m)', 'Max Tow Depth (m)', 'Min Tow Depth (m)',\n",
       "       'Vol Filtered (m3)', 'Broad Group', 'Mid-Level Group', '1st Word Taxa',\n",
       "       'Genus species', 'Life History Stage', 'Total Ct', 'Ind Carbon (ug)',\n",
       "       'Density (#/m3)', 'Final Carbon (mg/m3)',\n",
       "       'Species Size Category Aggregation', 'Size Category Aggregation',\n",
       "       'Collection Confidence', 'Carbon Regression EQ', 'C to DW multipier',\n",
       "       'DW Regression Equation', 'C/DW Source'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(labels=['BugSampleID','Project','Sampling Group','Date Category','Tow Type','Species Size Category Aggregation','Collection Confidence','Carbon Regression EQ','C to DW multipier','DW Regression Equation','C/DW Source'\n",
    "                       ],axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Sample Code</th>\n",
       "      <th>Station</th>\n",
       "      <th>Site Name</th>\n",
       "      <th>Basin</th>\n",
       "      <th>Sub Basin</th>\n",
       "      <th>Latitude</th>\n",
       "      <th>Longitude</th>\n",
       "      <th>Sample Date</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Sample Month</th>\n",
       "      <th>...</th>\n",
       "      <th>Broad Group</th>\n",
       "      <th>Mid-Level Group</th>\n",
       "      <th>1st Word Taxa</th>\n",
       "      <th>Genus species</th>\n",
       "      <th>Life History Stage</th>\n",
       "      <th>Total Ct</th>\n",
       "      <th>Ind Carbon (ug)</th>\n",
       "      <th>Density (#/m3)</th>\n",
       "      <th>Final Carbon (mg/m3)</th>\n",
       "      <th>Size Category Aggregation</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>060817HCB004V1454</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>2017-06-08</td>\n",
       "      <td>2017</td>\n",
       "      <td>JUN</td>\n",
       "      <td>...</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipoda-Hyperiidea</td>\n",
       "      <td>HYPEROCHE</td>\n",
       "      <td>HYPEROCHE</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>76.0</td>\n",
       "      <td>122.333000</td>\n",
       "      <td>5.169013</td>\n",
       "      <td>3.185477</td>\n",
       "      <td>Amphipod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>060817HCB004V1454</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>2017-06-08</td>\n",
       "      <td>2017</td>\n",
       "      <td>JUN</td>\n",
       "      <td>...</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipoda-Hyperiidea</td>\n",
       "      <td>HYPERIA</td>\n",
       "      <td>HYPERIA</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>1.0</td>\n",
       "      <td>107.303200</td>\n",
       "      <td>0.068013</td>\n",
       "      <td>0.010533</td>\n",
       "      <td>Amphipod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>060817HCB004V1454</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>2017-06-08</td>\n",
       "      <td>2017</td>\n",
       "      <td>JUN</td>\n",
       "      <td>...</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipoda-Hyperiidea</td>\n",
       "      <td>THEMISTO</td>\n",
       "      <td>THEMISTO PACIFICA</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>320.0</td>\n",
       "      <td>17.764660</td>\n",
       "      <td>21.764267</td>\n",
       "      <td>0.397324</td>\n",
       "      <td>Amphipod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>030917HCB003V1218</td>\n",
       "      <td>HCB003V</td>\n",
       "      <td>Eldon</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.53787</td>\n",
       "      <td>-123.0096</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>2017</td>\n",
       "      <td>MAR</td>\n",
       "      <td>...</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipoda-Cyphocarididae</td>\n",
       "      <td>CYPHOCARIS</td>\n",
       "      <td>CYPHOCARIS CHALLENGERI</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>66.0</td>\n",
       "      <td>343.152100</td>\n",
       "      <td>1.730036</td>\n",
       "      <td>0.564992</td>\n",
       "      <td>Amphipod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>030917HCB003V1218</td>\n",
       "      <td>HCB003V</td>\n",
       "      <td>Eldon</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.53787</td>\n",
       "      <td>-123.0096</td>\n",
       "      <td>2017-03-09</td>\n",
       "      <td>2017</td>\n",
       "      <td>MAR</td>\n",
       "      <td>...</td>\n",
       "      <td>Amphipod</td>\n",
       "      <td>Amphipoda-Hyperiidea</td>\n",
       "      <td>THEMISTO</td>\n",
       "      <td>THEMISTO PACIFICA</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>31.0</td>\n",
       "      <td>17.764660</td>\n",
       "      <td>0.812593</td>\n",
       "      <td>0.090677</td>\n",
       "      <td>Amphipod</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81582</th>\n",
       "      <td>050615MUKV1200</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>2015-05-06</td>\n",
       "      <td>2015</td>\n",
       "      <td>MAY</td>\n",
       "      <td>...</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>EGG Lg</td>\n",
       "      <td>4500.0</td>\n",
       "      <td>7.450710</td>\n",
       "      <td>98.804469</td>\n",
       "      <td>0.252324</td>\n",
       "      <td>Unknown Egg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81583</th>\n",
       "      <td>081315MUKV1121</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>2015-08-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>AUG</td>\n",
       "      <td>...</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>EGG Lg</td>\n",
       "      <td>385.0</td>\n",
       "      <td>7.450710</td>\n",
       "      <td>8.634707</td>\n",
       "      <td>0.011568</td>\n",
       "      <td>Unknown Egg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81584</th>\n",
       "      <td>082615MUKV1116</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>2015-08-26</td>\n",
       "      <td>2015</td>\n",
       "      <td>SEP</td>\n",
       "      <td>...</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>EGG Med</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>2.868051</td>\n",
       "      <td>27.045302</td>\n",
       "      <td>0.077567</td>\n",
       "      <td>Unknown Egg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81585</th>\n",
       "      <td>050615CAMV1305</td>\n",
       "      <td>CAMV</td>\n",
       "      <td>Camano Head</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>48.05901</td>\n",
       "      <td>-122.3873</td>\n",
       "      <td>2015-05-06</td>\n",
       "      <td>2015</td>\n",
       "      <td>MAY</td>\n",
       "      <td>...</td>\n",
       "      <td>Unknown Egg</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>EGG Lg</td>\n",
       "      <td>2025.0</td>\n",
       "      <td>7.450710</td>\n",
       "      <td>43.628610</td>\n",
       "      <td>0.325064</td>\n",
       "      <td>Unknown Egg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81586</th>\n",
       "      <td>080318HCB004V1114</td>\n",
       "      <td>HCB004V</td>\n",
       "      <td>Sisters Point</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>S Hood Canal</td>\n",
       "      <td>47.35620</td>\n",
       "      <td>-123.0249</td>\n",
       "      <td>2018-08-03</td>\n",
       "      <td>2018</td>\n",
       "      <td>AUG</td>\n",
       "      <td>...</td>\n",
       "      <td>Unknown Nauplius</td>\n",
       "      <td>Unknown</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>UNKNOWN</td>\n",
       "      <td>Nauplius</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>4.105091</td>\n",
       "      <td>0.004105</td>\n",
       "      <td>Unknown Nauplius</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81587 rows × 27 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Sample Code  Station      Site Name          Basin  \\\n",
       "0      060817HCB004V1454  HCB004V  Sisters Point     Hood Canal   \n",
       "1      060817HCB004V1454  HCB004V  Sisters Point     Hood Canal   \n",
       "2      060817HCB004V1454  HCB004V  Sisters Point     Hood Canal   \n",
       "3      030917HCB003V1218  HCB003V          Eldon     Hood Canal   \n",
       "4      030917HCB003V1218  HCB003V          Eldon     Hood Canal   \n",
       "...                  ...      ...            ...            ...   \n",
       "81582     050615MUKV1200     MUKV       Mukilteo  Whidbey Basin   \n",
       "81583     081315MUKV1121     MUKV       Mukilteo  Whidbey Basin   \n",
       "81584     082615MUKV1116     MUKV       Mukilteo  Whidbey Basin   \n",
       "81585     050615CAMV1305     CAMV    Camano Head  Whidbey Basin   \n",
       "81586  080318HCB004V1114  HCB004V  Sisters Point     Hood Canal   \n",
       "\n",
       "             Sub Basin  Latitude  Longitude Sample Date  Sample Year  \\\n",
       "0         S Hood Canal  47.35620  -123.0249  2017-06-08         2017   \n",
       "1         S Hood Canal  47.35620  -123.0249  2017-06-08         2017   \n",
       "2         S Hood Canal  47.35620  -123.0249  2017-06-08         2017   \n",
       "3         S Hood Canal  47.53787  -123.0096  2017-03-09         2017   \n",
       "4         S Hood Canal  47.53787  -123.0096  2017-03-09         2017   \n",
       "...                ...       ...        ...         ...          ...   \n",
       "81582  S Whidbey Basin  47.97166  -122.3222  2015-05-06         2015   \n",
       "81583  S Whidbey Basin  47.97166  -122.3222  2015-08-13         2015   \n",
       "81584  S Whidbey Basin  47.97166  -122.3222  2015-08-26         2015   \n",
       "81585  S Whidbey Basin  48.05901  -122.3873  2015-05-06         2015   \n",
       "81586     S Hood Canal  47.35620  -123.0249  2018-08-03         2018   \n",
       "\n",
       "      Sample Month  ...       Broad Group           Mid-Level Group  \\\n",
       "0              JUN  ...          Amphipod      Amphipoda-Hyperiidea   \n",
       "1              JUN  ...          Amphipod      Amphipoda-Hyperiidea   \n",
       "2              JUN  ...          Amphipod      Amphipoda-Hyperiidea   \n",
       "3              MAR  ...          Amphipod  Amphipoda-Cyphocarididae   \n",
       "4              MAR  ...          Amphipod      Amphipoda-Hyperiidea   \n",
       "...            ...  ...               ...                       ...   \n",
       "81582          MAY  ...       Unknown Egg                   Unknown   \n",
       "81583          AUG  ...       Unknown Egg                   Unknown   \n",
       "81584          SEP  ...       Unknown Egg                   Unknown   \n",
       "81585          MAY  ...       Unknown Egg                   Unknown   \n",
       "81586          AUG  ...  Unknown Nauplius                   Unknown   \n",
       "\n",
       "       1st Word Taxa           Genus species  Life History Stage  Total Ct  \\\n",
       "0          HYPEROCHE               HYPEROCHE             Unknown      76.0   \n",
       "1            HYPERIA                 HYPERIA             Unknown       1.0   \n",
       "2           THEMISTO       THEMISTO PACIFICA             Unknown     320.0   \n",
       "3         CYPHOCARIS  CYPHOCARIS CHALLENGERI             Unknown      66.0   \n",
       "4           THEMISTO       THEMISTO PACIFICA             Unknown      31.0   \n",
       "...              ...                     ...                 ...       ...   \n",
       "81582        UNKNOWN                 UNKNOWN              EGG Lg    4500.0   \n",
       "81583        UNKNOWN                 UNKNOWN              EGG Lg     385.0   \n",
       "81584        UNKNOWN                 UNKNOWN             EGG Med    1000.0   \n",
       "81585        UNKNOWN                 UNKNOWN              EGG Lg    2025.0   \n",
       "81586        UNKNOWN                 UNKNOWN            Nauplius      50.0   \n",
       "\n",
       "       Ind Carbon (ug) Density (#/m3) Final Carbon (mg/m3)  \\\n",
       "0           122.333000       5.169013             3.185477   \n",
       "1           107.303200       0.068013             0.010533   \n",
       "2            17.764660      21.764267             0.397324   \n",
       "3           343.152100       1.730036             0.564992   \n",
       "4            17.764660       0.812593             0.090677   \n",
       "...                ...            ...                  ...   \n",
       "81582         7.450710      98.804469             0.252324   \n",
       "81583         7.450710       8.634707             0.011568   \n",
       "81584         2.868051      27.045302             0.077567   \n",
       "81585         7.450710      43.628610             0.325064   \n",
       "81586         0.200000       4.105091             0.004105   \n",
       "\n",
       "      Size Category Aggregation  \n",
       "0                      Amphipod  \n",
       "1                      Amphipod  \n",
       "2                      Amphipod  \n",
       "3                      Amphipod  \n",
       "4                      Amphipod  \n",
       "...                         ...  \n",
       "81582               Unknown Egg  \n",
       "81583               Unknown Egg  \n",
       "81584               Unknown Egg  \n",
       "81585               Unknown Egg  \n",
       "81586          Unknown Nauplius  \n",
       "\n",
       "[81587 rows x 27 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Sample Code', 'Station', 'Site Name', 'Basin', 'Sub Basin', 'Latitude',\n",
       "       'Longitude', 'Sample Date', 'Sample Year', 'Sample Month',\n",
       "       'Sample Time', 'Mesh Size', 'Diameter (cm)', 'Station Depth (m)',\n",
       "       'Max Tow Depth (m)', 'Min Tow Depth (m)', 'Vol Filtered (m3)',\n",
       "       'Broad Group', 'Mid-Level Group', '1st Word Taxa', 'Genus species',\n",
       "       'Life History Stage', 'Total Ct', 'Ind Carbon (ug)', 'Density (#/m3)',\n",
       "       'Final Carbon (mg/m3)', 'Size Category Aggregation'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Amphipod', 'Amphipod Egg', 'Anthozoan', 'Arachnida', 'Barnacles',\n",
       "       'Bivalve', 'Bryozoan', 'Cephalopod', 'Chaetognath',\n",
       "       'Chaetognath Egg', 'Cladocera', 'Copepod', 'Copepod Egg',\n",
       "       'Copepod Nauplius', 'Crabs', 'Ctenophore', 'Cumacea',\n",
       "       'Dinoflagellate', 'Echinoderm', 'Fish', 'Fish Egg', 'Gastropod',\n",
       "       'Hydrozoan', 'Insect', 'Isopod', 'Krill Egg', 'Krill Nauplius',\n",
       "       'Krill-Adult Juvenile', 'Krill-Calyptopis', 'Krill-Furcilia',\n",
       "       'Larvacea', 'Mollusk Egg', 'Mysid', 'Mysid Egg', 'Nematode',\n",
       "       'Nemertea', 'Nudibranch', 'Ostracod', 'Phoronid',\n",
       "       'Platyhelminthes', 'Polychaete', 'Pycnogonida', 'Scyphozoan',\n",
       "       'Shrimp', 'Siphonophore', 'Siphonophore Gonophore', 'Tunicate',\n",
       "       'Tunicate Egg', 'Unknown', 'Unknown Egg', 'Unknown Nauplius'],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Broad Group'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "cala=df.loc[df['Broad Group']=='Copepod']\n",
    "euph=df.loc[df['Broad Group']=='Krill-Adult Juvenile']\n",
    "amph=df.loc[df['Broad Group']=='Amphipod']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "monthcala=cala.groupby(['Sample Month'], as_index=False).mean()\n",
    "montheuph=euph.groupby(['Sample Month'], as_index=False).mean()\n",
    "monthamph=amph.groupby(['Sample Month'], as_index=False).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 2.0)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(20,5))\n",
    "ax.plot(monthcala['Sample Month'],monthcala['Final Carbon (mg/m3)'],'-')\n",
    "ax.plot(montheuph['Sample Month'],montheuph['Final Carbon (mg/m3)'],'--')\n",
    "ax.plot(monthamph['Sample Month'],monthamph['Final Carbon (mg/m3)'],'-.')\n",
    "ax.set_ylim(0,2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Amphipoda-Hyperiidea', 'Amphipoda-Cyphocarididae',\n",
       "       'Amphipoda-Calliopiidae', 'Amphipoda-Gammaridae', 'Amphipoda',\n",
       "       'Amphipoda-Corophiidae', 'Amphipoda-Caprellidae',\n",
       "       'Cnidaria-Anthozoa', 'Arachnidae', 'Maxillopoda-Cirripedia',\n",
       "       'Bivalvia', 'Bryozoa', 'Cephalopoda-Octopus', 'Cephalopoda-Squid',\n",
       "       'Chaetognatha', 'Cladocera', 'Copepoda-Calanoida',\n",
       "       'Copepoda-Poecilostomatoida', 'Copepoda-Cyclopoida',\n",
       "       'Copepoda-Monstrilloida', 'Copepoda-Harpacticoida',\n",
       "       'Copepoda-Siphonostomatoida', 'Copepoda',\n",
       "       'Decapoda-Brachyura-Cancridae', 'Decapoda-Brachyura-Pinnotheridae',\n",
       "       'Decapoda-Anomura-Paguridae', 'Decapoda-Brachyura-Grapsoidea',\n",
       "       'Decapoda-Anomura-Galatheoidea', 'Decapoda-Brachyura-Majoidea',\n",
       "       'Decapoda-Brachyura-Xanthoidea', 'Decapoda-Anomura-Lithoidea',\n",
       "       'Decapoda-Brachyura', 'Decapoda-Brachyura-cheiragonidae',\n",
       "       'Decapoda-Anomura-Porcellanidae', 'Decapoda-Anomura', 'Ctenophora',\n",
       "       'Cumacea', 'Dinoflagellata', 'Echinodermata', 'Chordata-Fish',\n",
       "       'Gastropoda', 'Cnidaria-Hydrozoa-Leptothecata',\n",
       "       'Cnidaria-Hydrozoa-Trachymedusa',\n",
       "       'Cnidaria-Hydrozoa-Anthoathecata-Pandeidea',\n",
       "       'Cnidaria-Hydrozoa-Anthoathecata', 'Cnidaria-Hydrozoa-Limnomedusa',\n",
       "       'Cnidaria-Hydrozoa', 'Cnidaria-Hydrozoa-Narcomedusa', 'Insecta',\n",
       "       'Isopoda', 'Euphausiidae', 'Euphausiidae-EUPHAUSIA-Nauplii',\n",
       "       'Euphausiidae-Nauplii', 'Euphausiidae-THYSANOESSA-Nauplii',\n",
       "       'Euphausiidae-EUPHAUSIA-Adult', 'Euphausiidae-THYSANOESSA-Adult',\n",
       "       'Euphausiidae-NEMATOSCELIS-Adult',\n",
       "       'Euphausiidae-EUPHAUSIA-Calyptopes',\n",
       "       'Euphausiidae-THYSANOESSA-Calyptopes', 'Euphausiidae-Calyptopes',\n",
       "       'Euphausiidae-EUPHAUSIA-Furcillia',\n",
       "       'Euphausiidae-THYSANOESSA-Furcillia', 'Euphausiidae-Furcillia',\n",
       "       'Chordata-Larvacea', 'Mollusca', 'Mysida', 'Nematoda', 'Nemertea',\n",
       "       'Nudibranchia', 'Ostracoda', 'Phoronid', 'Platyhelminthes',\n",
       "       'Annelida-Polychaeta', 'Pycnogonida', 'Cnidaria-Scyphozoa',\n",
       "       'Decapoda-Caridea-Hippolytidae', 'Decapoda-Caridea-Callianassidae',\n",
       "       'Decapoda-Caridea-Crangonidae', 'Decapoda-Caridea-Pandalidae',\n",
       "       'Decapoda-Caridea-Pasiphaeaidae', 'Decapoda-Caridea',\n",
       "       'Decapoda-Gebiidea', 'Decapoda-Caridea-Sergestidae',\n",
       "       'Cnidaria-Siphonophore-Calycophoran',\n",
       "       'Cnidaria-Siphonophore-Physonect', 'Cnidaria-Siphonophore',\n",
       "       'Chordata-Tunicata', 'Unknown'], dtype=object)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Mid-Level Group'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#colListBroad=('Amphipoda', 'Crabs','Krill-Adult Juvenile','Krill-Calyptopis','Krill-Furcilia','Copepod', 'Larvacea',)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "colListMid=('Amphipoda-Hyperiidea', 'Amphipoda-Cyphocarididae',\n",
    "       'Amphipoda-Calliopiidae', 'Amphipoda-Gammaridae', 'Amphipoda',\n",
    "       'Amphipoda-Corophiidae', 'Amphipoda-Caprellidae','Copepoda-Calanoida','Copepoda-Poecilostomatoida', 'Copepoda-Cyclopoida',\n",
    "       'Copepoda-Monstrilloida', 'Copepoda-Harpacticoida',\n",
    "       'Copepoda-Siphonostomatoida','Decapoda-Brachyura-Cancridae', 'Decapoda-Brachyura-Pinnotheridae',\n",
    "       'Decapoda-Anomura-Paguridae', 'Decapoda-Brachyura-Grapsoidea',\n",
    "       'Decapoda-Anomura-Galatheoidea', 'Decapoda-Brachyura-Majoidea',\n",
    "       'Decapoda-Brachyura-Xanthoidea', 'Decapoda-Anomura-Lithoidea',\n",
    "       'Decapoda-Brachyura', 'Decapoda-Brachyura-cheiragonidae',\n",
    "       'Decapoda-Anomura-Porcellanidae', 'Decapoda-Anomura','Gastropoda','Euphausiidae', 'Euphausiidae-EUPHAUSIA-Nauplii',\n",
    "       'Euphausiidae-Nauplii', 'Euphausiidae-THYSANOESSA-Nauplii',\n",
    "       'Euphausiidae-EUPHAUSIA-Adult', 'Euphausiidae-THYSANOESSA-Adult',\n",
    "       'Euphausiidae-NEMATOSCELIS-Adult',\n",
    "       'Euphausiidae-EUPHAUSIA-Calyptopes',\n",
    "       'Euphausiidae-THYSANOESSA-Calyptopes', 'Euphausiidae-Calyptopes',\n",
    "       'Euphausiidae-EUPHAUSIA-Furcillia',\n",
    "       'Euphausiidae-THYSANOESSA-Furcillia', 'Euphausiidae-Furcillia',\n",
    "       'Chordata-Larvacea','Cnidaria-Scyphozoa','Cnidaria-Siphonophore-Calycophoran',\n",
    "       'Cnidaria-Siphonophore-Physonect', 'Cnidaria-Siphonophore',\n",
    "       'Chordata-Tunicata')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "#colListGenus=('METRIDIA PACIFICA','NEOCALANUS PLUMCHRUS','CALANOIDA','EUCALANUS BUNGII','CALANUS PACIFICUS','CALANUS MARSHALLAE','NEOCALANUS CRISTATUS','EUCALANUS CALIFORNICUS','EUCALANUS','METRIDIIDAE','NEOCALANUS')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "#l1=set(df['order'].values)\n",
    "#l2=set(df['genus species'].values)\n",
    "#l3=l1|l2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['HYPEROCHE', 'HYPERIA', 'THEMISTO PACIFICA',\n",
       "       'CYPHOCARIS CHALLENGERI', 'PRIMNO MACROPA', 'CALLIOPIUS PACIFICUS',\n",
       "       'HYPERIIDEA', 'GAMMARIDEA', 'AMPHIPODA', 'COROPHIUM',\n",
       "       'CAPRELLIDAE', 'CALLIOPIUS CARINATUS', 'PARAPHRONIMA CRASSIPES',\n",
       "       'Anthozoa', 'PEACHIA', 'MITES', 'Arachnidae', 'BARNACLES',\n",
       "       'BIVALVIA', 'BRYOZOA', 'OCTOPODA', 'Teuthida', 'CHAETOGNATHA',\n",
       "       'Chaet/Euphaus Egg', 'EVADNE', 'PODON', 'Evadne', 'CLADOCERA',\n",
       "       'ACARTIA HUDSONICA', 'ACARTIA LONGIREMIS', 'AETIDEUS',\n",
       "       'CENTROPAGES ABDOMINALIS', 'DITRICHOCORYCAEUS ANGLICUS',\n",
       "       'METRIDIA PACIFICA', 'MICROCALANUS', 'OITHONA SIMILIS',\n",
       "       'PARACALANUS', 'PSEUDOCALANUS', 'SCOLECITHRICELLA MINOR',\n",
       "       'PARAEUCHAETA ELONGATA', 'CANDACIA COLUMBIAE',\n",
       "       'CHIRIDIUS GRACILIS', 'OITHONA ATLANTICA', 'PSEUDOCALANUS NEWMANI',\n",
       "       'PSEUDOCALANUS MOULTONI', 'PSEUDOCALANUS Sm', 'THARYBIS FULTONI',\n",
       "       'TRICONIA MINUTA', 'Monstrilloida', 'HARPACTICOIDA',\n",
       "       'GAETANUS PUNGENS', 'NEOCALANUS PLUMCHRUS', 'CALANOIDA',\n",
       "       'TRICONIA CONIFERA', 'EUCALANUS BUNGII', 'TRICONIA BOREALIS',\n",
       "       'OITHONA', 'CALANUS PACIFICUS', 'CALANUS MARSHALLAE',\n",
       "       'TORTANUS DISCAUDATUS', 'PSEUDOCALANUS MIMUS', 'ACARTIA TONSA',\n",
       "       'ONCAEA SUBTILIS', 'Siphonostomatoida', 'ONCAEIDAE',\n",
       "       'BRADYIDIUS SAANICHI', 'PSEUDOCALANUS Lg', 'TRICONIA CANADENSIS',\n",
       "       'NEOCALANUS CRISTATUS', 'PSEUDOCALANUS MINUTUS',\n",
       "       'RACOVITZANUS ANTARCTICUS', 'ACARTIA', 'HEMICYCLOPS',\n",
       "       'ONCAEA PROLATA', 'EPILABIDOCERA AMPHITRITES',\n",
       "       'CTENOCALANUS VANUS', 'SCOLECITHRICELLA OVATA', 'HETERORHABDUS',\n",
       "       'EUCALANUS CALIFORNICUS', 'CYCLOPOIDA', 'TRICONIA SIMILIS',\n",
       "       'SCOLECITHRICELLA Minor', 'Chiridius gracilis', 'GAETANUS SIMPLEX',\n",
       "       'CANDACIA BIPINNATA', 'CANDACIA', 'EUCHIRELLA PULCHRA',\n",
       "       'AETIDEUS ARMATUS', 'TRICONIA', 'GAETANUS MINUTUS', 'EURYTEMORA',\n",
       "       'MESOCALANUS TENUICORNIS', 'EUCALANUS', 'CLAUSOCALANUS',\n",
       "       'SCOLECITHRICELLA DENTATA', 'SCOLECITHRICELLA',\n",
       "       'PLEUROMAMMA ABDOMINALIS', 'Poecilostomatoida',\n",
       "       'EUCHIRELLA PSEUDOPULCHRA', 'EUCHAETIDAE',\n",
       "       'SCAPHOCALANUS BREVICORNIS', 'METRIDIIDAE', 'COPEPODA',\n",
       "       'NEOCALANUS', 'PLEUROMAMMA', 'GAETANUS MILES', 'TRICONIA (tiny)',\n",
       "       'AETIDEUS DIVERGENS', 'CALIGIDAE', 'FARRANULA', 'TORTANUS',\n",
       "       'Tortanus', 'METACARCINUS MAGISTER', 'GLEBOCARCINUS OREGONENSIS',\n",
       "       'METACARCINUS GRACILIS', 'PINNIXA', 'PAGURUS', 'HEMIGRAPSUS',\n",
       "       'GALATHEIDAE', 'PUGETTIA', 'LOPHOPANOPEUS BELLUS',\n",
       "       'CANCER PRODUCTUS', 'FABIA SUBQUADRATA', 'LITHODIDAE',\n",
       "       'OREGONIA GRACILIS', 'PINNOTHERES', 'BRACHYURA', 'Galatheidae',\n",
       "       'Cancridae Sm', 'PINNOTHERIDAE', 'CANCRIDAE',\n",
       "       'Telmessus cheiragonus', 'XANTHOIDEA', 'PACHYCHELES',\n",
       "       'PETROLISTHES', 'Cancridae Lg', 'MAJOIDEA', 'LOPHOLITHODES',\n",
       "       'CHIONOECETES', 'PORCELLANIDAE', 'PAGURIDAE', 'RHINOLITHODES',\n",
       "       'GRAPSIDAE', 'CRYPTOLITHODES', 'DIOGENIDAE', 'ANOMURA',\n",
       "       'PLEUROBRACHIA BACHEI', 'CTENOPHORA', 'Pleurobrachia bachei',\n",
       "       'BEROE', 'CUMACEA', 'NOCTILUCA', 'ECHINODERMATA', 'HOLOTHUROIDEA',\n",
       "       'OPHIUROIDEA', 'FISH', 'Forage FISH', 'Syngnathidae', 'Fish',\n",
       "       'LIMACINA HELICINA', 'CLIONE LIMACINA', 'GASTROPODA',\n",
       "       'GASTROPTERON PACIFICUM', 'Limacina helicina', 'AEQUOREA VICTORIA',\n",
       "       'Mitrocoma cellularia', 'AGLANTHA DIGITALE', 'PANDEIDAE',\n",
       "       'EUPHYSA', 'PROBOSCIDACTYLA FLAVICIRRATA', 'HALITHOLUS', 'RATHKEA',\n",
       "       'OBELIA', 'EUTONINA INDICANS', 'CLYTIA GREGARIA', 'SARSIA',\n",
       "       'LEPTOTHECATA', 'LEUCKARTIARA', 'ANTHOATHECATA', 'HYDROMEDUSA',\n",
       "       'Clytia gregaria', 'Aglantha digitale', 'HYDROID',\n",
       "       'Geomackiea zephyrolata', 'AMPHINEMA', 'AEGINA CITREA',\n",
       "       'STOMOTOCA ATRA', 'BOUGAINVILLIA', 'Euphysa', 'SOLMISSUS',\n",
       "       'HYBOCODON', 'NARCOMEDUSIDA', 'MITROCOMELLA', 'TIAROPSIS',\n",
       "       'HYDROZOA', 'Insecta', 'ISOPODA', 'EUPHAUSIIDAE',\n",
       "       'EUPHAUSIA PACIFICA', 'THYSANOESSA', 'THYSANOESSA RASCHII',\n",
       "       'NEMATOSCELIS DIFFICILIS', 'THYSANOESSA SPINIFERA',\n",
       "       'THYSANOESSA LONGIPES', 'FRITILLARIA', 'OIKOPLEURA', 'LARVACEA',\n",
       "       'LITTORINA', 'ALIENACANTHOMYSIS MACROPSIS',\n",
       "       'METERYTHROPS ROBUSTUS', 'PACIFACANTHOMYSIS NEPHROPHTHALMA',\n",
       "       'MYSIDELLA AMERICANA', 'MYSIDACEA',\n",
       "       'XENACANTHOMYSIS PSEUDOMACROPSIS', 'NEOMYSIS',\n",
       "       'Exacanthomysis davisi', 'PSEUDOMMA', 'NEOMYSIS MERCEDIS',\n",
       "       'NEMATODA', 'Nemertea', 'NUDIBRANCHIA', 'OSTRACODA', 'PHORONIDA',\n",
       "       'PLATYHELMINTHES', 'POLYCHAETA', 'RHYNCHONEREELLA ANGELINI',\n",
       "       'OWENIA', 'TOMOPTERIS', 'PYCNOGONIDA', 'SCYPHOMEDUSA',\n",
       "       'HIPPOLYTIDAE', 'NEOTRYPAEA CALIFORNIENSIS', 'CRANGONIDAE',\n",
       "       'PANDALUS STENOLEPIS', 'PASIPHAEA PACIFICA', 'CALLIANASSIDAE',\n",
       "       'PANDALIDAE', 'CARIDEA', 'UPOGEBIIDAE', 'Caridea',\n",
       "       'SERGESTES SIMILIS', 'DECAPODA', 'MUGGIAEA ATLANTICA',\n",
       "       'Nanomia bijuga', 'Muggiaea atlantica', 'Physonect', 'DIMOPHYES',\n",
       "       'CALYCOPHORAE', 'SIPHONOPHORA', 'ASCIDIACEA', 'SALPA', 'UNKNOWN',\n",
       "       'Unknown'], dtype=object)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Genus species'].unique()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert date to proper format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Timestamp('2017-06-08 00:00:00'), datetime.time(14, 54))"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Sample Date'][0],df['Sample Time'][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000   2015-08-04\n",
       "1001   2015-08-04\n",
       "1002   2015-08-04\n",
       "1003   2015-08-04\n",
       "1004   2015-08-17\n",
       "1005   2015-08-17\n",
       "1006   2015-08-17\n",
       "1007   2015-08-18\n",
       "1008   2015-08-18\n",
       "1009   2015-08-18\n",
       "1010   2015-08-18\n",
       "1011   2015-08-18\n",
       "1012   2015-07-20\n",
       "1013   2015-07-20\n",
       "1014   2015-07-20\n",
       "1015   2015-08-03\n",
       "1016   2015-08-03\n",
       "1017   2015-08-03\n",
       "1018   2015-07-06\n",
       "1019   2015-07-06\n",
       "Name: Sample Date, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Sample Date'][1000:1020]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['dtPac']=[dt.datetime.combine(idate, itime) for idate, itime \\\n",
    "                 in zip(df['Sample Date'],df['Sample Time'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['dtUTC']=[et.pac_to_utc(ii) for ii in df['dtPac']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       2017-06-08 21:54:00\n",
       "1       2017-06-08 21:54:00\n",
       "2       2017-06-08 21:54:00\n",
       "3       2017-03-09 20:18:00\n",
       "4       2017-03-09 20:18:00\n",
       "                ...        \n",
       "81582   2015-05-06 19:00:00\n",
       "81583   2015-08-13 18:21:00\n",
       "81584   2015-08-26 18:16:00\n",
       "81585   2015-05-06 20:05:00\n",
       "81586   2018-08-03 18:14:00\n",
       "Name: dtUTC, Length: 81587, dtype: datetime64[ns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['dtUTC']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Sample Month']=[ii.month for ii in df['dtUTC']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={'Sample Code':'Key','Latitude':'Lat','Longitude':'Lon'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Key                             060817HCB004V1454\n",
       "Station                                   HCB004V\n",
       "Site Name                           Sisters Point\n",
       "Basin                                  Hood Canal\n",
       "Sub Basin                            S Hood Canal\n",
       "Lat                                       47.3562\n",
       "Lon                                     -123.0249\n",
       "Sample Date                   2017-06-08 00:00:00\n",
       "Sample Year                                  2017\n",
       "Sample Month                                    6\n",
       "Sample Time                              14:54:00\n",
       "Mesh Size                                     200\n",
       "Diameter (cm)                                60.0\n",
       "Station Depth (m)                            52.0\n",
       "Max Tow Depth (m)                            47.0\n",
       "Min Tow Depth (m)                               0\n",
       "Vol Filtered (m3)                       14.702999\n",
       "Broad Group                              Amphipod\n",
       "Mid-Level Group              Amphipoda-Hyperiidea\n",
       "1st Word Taxa                           HYPEROCHE\n",
       "Genus species                           HYPEROCHE\n",
       "Life History Stage                        Unknown\n",
       "Total Ct                                     76.0\n",
       "Ind Carbon (ug)                           122.333\n",
       "Density (#/m3)                           5.169013\n",
       "Final Carbon (mg/m3)                     3.185477\n",
       "Size Category Aggregation                Amphipod\n",
       "dtPac                         2017-06-08 14:54:00\n",
       "dtUTC                         2017-06-08 21:54:00\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "towIDlist=['Key','Station', 'Site Name', 'Basin', 'Sub Basin', 'Lat',\n",
    "       'Lon', 'Sample Date', 'Sample Year', 'Sample Month',\n",
    "       'Sample Time', 'Mesh Size', 'Diameter (cm)', 'Station Depth (m)',\n",
    "       'Max Tow Depth (m)', 'Min Tow Depth (m)','dtUTC']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "towIDlist2=['Key', 'Station', 'Sample Date','Sample Time','dtUTC']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2168, 1159, 1159)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df.groupby(towIDlist)),len(df.groupby(towIDlist2)),len(df.groupby(['Key']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a biomass dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomassDF=df.groupby(towIDlist2,as_index=False).first()\\\n",
    "     .loc[:,towIDlist].copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Key</th>\n",
       "      <th>Station</th>\n",
       "      <th>Site Name</th>\n",
       "      <th>Basin</th>\n",
       "      <th>Sub Basin</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Sample Date</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Sample Month</th>\n",
       "      <th>Sample Time</th>\n",
       "      <th>Mesh Size</th>\n",
       "      <th>Diameter (cm)</th>\n",
       "      <th>Station Depth (m)</th>\n",
       "      <th>Max Tow Depth (m)</th>\n",
       "      <th>Min Tow Depth (m)</th>\n",
       "      <th>dtUTC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>010218ELIV1151</td>\n",
       "      <td>ELIV</td>\n",
       "      <td>Eliza Island</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>48.63795</td>\n",
       "      <td>-122.5694</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>11:51:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>120.700</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-01-02 19:51:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>010818SKETV1058</td>\n",
       "      <td>SKETV</td>\n",
       "      <td>South Ketron/Solo Point</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>47.15243</td>\n",
       "      <td>-122.6586</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>10:58:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>132.000</td>\n",
       "      <td>122.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-01-08 18:58:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>011119ELIV1052</td>\n",
       "      <td>ELIV</td>\n",
       "      <td>Eliza Island</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>48.63795</td>\n",
       "      <td>-122.5694</td>\n",
       "      <td>2019-01-11</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>10:52:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>124.054</td>\n",
       "      <td>114.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2019-01-11 18:52:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>011315CAMV1330</td>\n",
       "      <td>CAMV</td>\n",
       "      <td>Camano Head</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>48.05901</td>\n",
       "      <td>-122.3873</td>\n",
       "      <td>2015-01-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>13:30:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>175.000</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015-01-13 21:30:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>011315MUKV1415</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>2015-01-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>14:15:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>200.000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2015-01-13 22:15:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1154</th>\n",
       "      <td>121917LSNT01V1000</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2017-12-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>10:00:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>210.000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2017-12-19 18:00:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1155</th>\n",
       "      <td>121917NSEX01V1224</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2017-12-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>12:24:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>180.000</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2017-12-19 20:24:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>121918TDBV1327</td>\n",
       "      <td>TDBV</td>\n",
       "      <td>Thorndyke Bay</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>N Hood Canal</td>\n",
       "      <td>47.78297</td>\n",
       "      <td>-122.7330</td>\n",
       "      <td>2018-12-19</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>13:27:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>112.000</td>\n",
       "      <td>109.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2018-12-19 21:27:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1157</th>\n",
       "      <td>122116LSNT01V1057</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>10:57:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>210.000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-12-21 18:57:00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1158</th>\n",
       "      <td>122116NSEX01V1237</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>12:37:00</td>\n",
       "      <td>200</td>\n",
       "      <td>60.0</td>\n",
       "      <td>180.000</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0</td>\n",
       "      <td>2016-12-21 20:37:00</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1159 rows × 17 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Key  Station                Site Name           Basin  \\\n",
       "0        010218ELIV1151     ELIV             Eliza Island  Bellingham Bay   \n",
       "1       010818SKETV1058    SKETV  South Ketron/Solo Point     South Sound   \n",
       "2        011119ELIV1052     ELIV             Eliza Island  Bellingham Bay   \n",
       "3        011315CAMV1330     CAMV              Camano Head   Whidbey Basin   \n",
       "4        011315MUKV1415     MUKV                 Mukilteo   Whidbey Basin   \n",
       "...                 ...      ...                      ...             ...   \n",
       "1154  121917LSNT01V1000  LSNT01V           Point Williams   Central Basin   \n",
       "1155  121917NSEX01V1224  NSEX01V             East Passage   Central Basin   \n",
       "1156     121918TDBV1327     TDBV            Thorndyke Bay      Hood Canal   \n",
       "1157  122116LSNT01V1057  LSNT01V           Point Williams   Central Basin   \n",
       "1158  122116NSEX01V1237  NSEX01V             East Passage   Central Basin   \n",
       "\n",
       "            Sub Basin       Lat       Lon Sample Date  Sample Year  \\\n",
       "0      Bellingham Bay  48.63795 -122.5694  2018-01-02         2018   \n",
       "1         South Sound  47.15243 -122.6586  2018-01-08         2018   \n",
       "2      Bellingham Bay  48.63795 -122.5694  2019-01-11         2019   \n",
       "3     S Whidbey Basin  48.05901 -122.3873  2015-01-13         2015   \n",
       "4     S Whidbey Basin  47.97166 -122.3222  2015-01-13         2015   \n",
       "...               ...       ...       ...         ...          ...   \n",
       "1154  N Central Basin  47.53333 -122.4333  2017-12-19         2017   \n",
       "1155  S Central Basin  47.35862 -122.3871  2017-12-19         2017   \n",
       "1156     N Hood Canal  47.78297 -122.7330  2018-12-19         2018   \n",
       "1157  N Central Basin  47.53333 -122.4333  2016-12-21         2016   \n",
       "1158  S Central Basin  47.35862 -122.3871  2016-12-21         2016   \n",
       "\n",
       "      Sample Month Sample Time  Mesh Size  Diameter (cm)  Station Depth (m)  \\\n",
       "0                1    11:51:00        200           60.0            120.700   \n",
       "1                1    10:58:00        200           60.0            132.000   \n",
       "2                1    10:52:00        200           60.0            124.054   \n",
       "3                1    13:30:00        200           60.0            175.000   \n",
       "4                1    14:15:00        200           60.0            200.000   \n",
       "...            ...         ...        ...            ...                ...   \n",
       "1154            12    10:00:00        200           60.0            210.000   \n",
       "1155            12    12:24:00        200           60.0            180.000   \n",
       "1156            12    13:27:00        200           60.0            112.000   \n",
       "1157            12    10:57:00        200           60.0            210.000   \n",
       "1158            12    12:37:00        200           60.0            180.000   \n",
       "\n",
       "      Max Tow Depth (m)  Min Tow Depth (m)               dtUTC  \n",
       "0                 110.0                  0 2018-01-02 19:51:00  \n",
       "1                 122.0                  0 2018-01-08 18:58:00  \n",
       "2                 114.0                  0 2019-01-11 18:52:00  \n",
       "3                 170.0                  0 2015-01-13 21:30:00  \n",
       "4                 190.0                  0 2015-01-13 22:15:00  \n",
       "...                 ...                ...                 ...  \n",
       "1154              200.0                  0 2017-12-19 18:00:00  \n",
       "1155              170.0                  0 2017-12-19 20:24:00  \n",
       "1156              109.0                  0 2018-12-19 21:27:00  \n",
       "1157              200.0                  0 2016-12-21 18:57:00  \n",
       "1158              170.0                  0 2016-12-21 20:37:00  \n",
       "\n",
       "[1159 rows x 17 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "#biomassDF2=biomassDF.loc[biomassDF['Sample Year']==2015].copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df2=df.loc[df['Sample Year']==2015].copy(deep=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getbiomass(colname,key,origdf,matchcol):        \n",
    "    biomassArray=origdf.loc[(origdf.Key==key)&(origdf[matchcol]==colname),\n",
    "                    ['Final Carbon (mg/m3)']]\n",
    "    biomass=np.nansum(biomassArray)\n",
    "    \n",
    "    return biomass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "for icol in colListMid:\n",
    "    biomassDF[icol]=[getbiomass(icol,ikey,df,'Mid-Level Group') for ikey in biomassDF['Key']]\n",
    " "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "   \n",
    "#for icol in colListGenus:\n",
    "   #biomassDF[icol]=[getbiomass(icol,ikey,df,'Genus species') for ikey in biomassDF['Key']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Key</th>\n",
       "      <th>Station</th>\n",
       "      <th>Site Name</th>\n",
       "      <th>Basin</th>\n",
       "      <th>Sub Basin</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Sample Date</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Sample Month</th>\n",
       "      <th>...</th>\n",
       "      <th>Euphausiidae-Calyptopes</th>\n",
       "      <th>Euphausiidae-EUPHAUSIA-Furcillia</th>\n",
       "      <th>Euphausiidae-THYSANOESSA-Furcillia</th>\n",
       "      <th>Euphausiidae-Furcillia</th>\n",
       "      <th>Chordata-Larvacea</th>\n",
       "      <th>Cnidaria-Scyphozoa</th>\n",
       "      <th>Cnidaria-Siphonophore-Calycophoran</th>\n",
       "      <th>Cnidaria-Siphonophore-Physonect</th>\n",
       "      <th>Cnidaria-Siphonophore</th>\n",
       "      <th>Chordata-Tunicata</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>010218ELIV1151</td>\n",
       "      <td>ELIV</td>\n",
       "      <td>Eliza Island</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>48.63795</td>\n",
       "      <td>-122.5694</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.010136</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>010818SKETV1058</td>\n",
       "      <td>SKETV</td>\n",
       "      <td>South Ketron/Solo Point</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>47.15243</td>\n",
       "      <td>-122.6586</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.122849</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.011965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>011119ELIV1052</td>\n",
       "      <td>ELIV</td>\n",
       "      <td>Eliza Island</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>48.63795</td>\n",
       "      <td>-122.5694</td>\n",
       "      <td>2019-01-11</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.003334</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>011315CAMV1330</td>\n",
       "      <td>CAMV</td>\n",
       "      <td>Camano Head</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>48.05901</td>\n",
       "      <td>-122.3873</td>\n",
       "      <td>2015-01-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.007484</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>011315MUKV1415</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>2015-01-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.012628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1154</th>\n",
       "      <td>121917LSNT01V1000</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2017-12-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.057153</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1155</th>\n",
       "      <td>121917NSEX01V1224</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2017-12-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.001806</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.178813</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.006617</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>121918TDBV1327</td>\n",
       "      <td>TDBV</td>\n",
       "      <td>Thorndyke Bay</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>N Hood Canal</td>\n",
       "      <td>47.78297</td>\n",
       "      <td>-122.7330</td>\n",
       "      <td>2018-12-19</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.007106</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.031724</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1157</th>\n",
       "      <td>122116LSNT01V1057</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.070042</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.014621</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1158</th>\n",
       "      <td>122116NSEX01V1237</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.132961</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.005358</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1159 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Key  Station                Site Name           Basin  \\\n",
       "0        010218ELIV1151     ELIV             Eliza Island  Bellingham Bay   \n",
       "1       010818SKETV1058    SKETV  South Ketron/Solo Point     South Sound   \n",
       "2        011119ELIV1052     ELIV             Eliza Island  Bellingham Bay   \n",
       "3        011315CAMV1330     CAMV              Camano Head   Whidbey Basin   \n",
       "4        011315MUKV1415     MUKV                 Mukilteo   Whidbey Basin   \n",
       "...                 ...      ...                      ...             ...   \n",
       "1154  121917LSNT01V1000  LSNT01V           Point Williams   Central Basin   \n",
       "1155  121917NSEX01V1224  NSEX01V             East Passage   Central Basin   \n",
       "1156     121918TDBV1327     TDBV            Thorndyke Bay      Hood Canal   \n",
       "1157  122116LSNT01V1057  LSNT01V           Point Williams   Central Basin   \n",
       "1158  122116NSEX01V1237  NSEX01V             East Passage   Central Basin   \n",
       "\n",
       "            Sub Basin       Lat       Lon Sample Date  Sample Year  \\\n",
       "0      Bellingham Bay  48.63795 -122.5694  2018-01-02         2018   \n",
       "1         South Sound  47.15243 -122.6586  2018-01-08         2018   \n",
       "2      Bellingham Bay  48.63795 -122.5694  2019-01-11         2019   \n",
       "3     S Whidbey Basin  48.05901 -122.3873  2015-01-13         2015   \n",
       "4     S Whidbey Basin  47.97166 -122.3222  2015-01-13         2015   \n",
       "...               ...       ...       ...         ...          ...   \n",
       "1154  N Central Basin  47.53333 -122.4333  2017-12-19         2017   \n",
       "1155  S Central Basin  47.35862 -122.3871  2017-12-19         2017   \n",
       "1156     N Hood Canal  47.78297 -122.7330  2018-12-19         2018   \n",
       "1157  N Central Basin  47.53333 -122.4333  2016-12-21         2016   \n",
       "1158  S Central Basin  47.35862 -122.3871  2016-12-21         2016   \n",
       "\n",
       "      Sample Month  ... Euphausiidae-Calyptopes  \\\n",
       "0                1  ...                     0.0   \n",
       "1                1  ...                     0.0   \n",
       "2                1  ...                     0.0   \n",
       "3                1  ...                     0.0   \n",
       "4                1  ...                     0.0   \n",
       "...            ...  ...                     ...   \n",
       "1154            12  ...                     0.0   \n",
       "1155            12  ...                     0.0   \n",
       "1156            12  ...                     0.0   \n",
       "1157            12  ...                     0.0   \n",
       "1158            12  ...                     0.0   \n",
       "\n",
       "      Euphausiidae-EUPHAUSIA-Furcillia  Euphausiidae-THYSANOESSA-Furcillia  \\\n",
       "0                             0.000000                                 0.0   \n",
       "1                             0.000000                                 0.0   \n",
       "2                             0.000000                                 0.0   \n",
       "3                             0.000000                                 0.0   \n",
       "4                             0.000000                                 0.0   \n",
       "...                                ...                                 ...   \n",
       "1154                          0.000000                                 0.0   \n",
       "1155                          0.001806                                 0.0   \n",
       "1156                          0.007106                                 0.0   \n",
       "1157                          0.000000                                 0.0   \n",
       "1158                          0.000000                                 0.0   \n",
       "\n",
       "      Euphausiidae-Furcillia  Chordata-Larvacea  Cnidaria-Scyphozoa  \\\n",
       "0                        0.0           0.010136                 0.0   \n",
       "1                        0.0           0.122849                 0.0   \n",
       "2                        0.0           0.003334                 0.0   \n",
       "3                        0.0           0.000000                 0.0   \n",
       "4                        0.0           0.012628                 0.0   \n",
       "...                      ...                ...                 ...   \n",
       "1154                     0.0           0.057153                 0.0   \n",
       "1155                     0.0           0.178813                 0.0   \n",
       "1156                     0.0           0.031724                 0.0   \n",
       "1157                     0.0           0.070042                 0.0   \n",
       "1158                     0.0           0.132961                 0.0   \n",
       "\n",
       "     Cnidaria-Siphonophore-Calycophoran  Cnidaria-Siphonophore-Physonect  \\\n",
       "0                              0.000000                              0.0   \n",
       "1                              0.011965                              0.0   \n",
       "2                              0.000000                              0.0   \n",
       "3                              0.007484                              0.0   \n",
       "4                              0.000000                              0.0   \n",
       "...                                 ...                              ...   \n",
       "1154                           0.000000                              0.0   \n",
       "1155                           0.006617                              0.0   \n",
       "1156                           0.000000                              0.0   \n",
       "1157                           0.014621                              0.0   \n",
       "1158                           0.005358                              0.0   \n",
       "\n",
       "      Cnidaria-Siphonophore  Chordata-Tunicata  \n",
       "0                       0.0                0.0  \n",
       "1                       0.0                0.0  \n",
       "2                       0.0                0.0  \n",
       "3                       0.0                0.0  \n",
       "4                       0.0                0.0  \n",
       "...                     ...                ...  \n",
       "1154                    0.0                0.0  \n",
       "1155                    0.0                0.0  \n",
       "1156                    0.0                0.0  \n",
       "1157                    0.0                0.0  \n",
       "1158                    0.0                0.0  \n",
       "\n",
       "[1159 rows x 62 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Key', 'Station', 'Site Name', 'Basin', 'Sub Basin', 'Lat', 'Lon',\n",
       "       'Sample Date', 'Sample Year', 'Sample Month', 'Sample Time',\n",
       "       'Mesh Size', 'Diameter (cm)', 'Station Depth (m)', 'Max Tow Depth (m)',\n",
       "       'Min Tow Depth (m)', 'dtUTC', 'Amphipoda-Hyperiidea',\n",
       "       'Amphipoda-Cyphocarididae', 'Amphipoda-Calliopiidae',\n",
       "       'Amphipoda-Gammaridae', 'Amphipoda', 'Amphipoda-Corophiidae',\n",
       "       'Amphipoda-Caprellidae', 'Copepoda-Calanoida',\n",
       "       'Copepoda-Poecilostomatoida', 'Copepoda-Cyclopoida',\n",
       "       'Copepoda-Monstrilloida', 'Copepoda-Harpacticoida',\n",
       "       'Copepoda-Siphonostomatoida', 'Decapoda-Brachyura-Cancridae',\n",
       "       'Decapoda-Brachyura-Pinnotheridae', 'Decapoda-Anomura-Paguridae',\n",
       "       'Decapoda-Brachyura-Grapsoidea', 'Decapoda-Anomura-Galatheoidea',\n",
       "       'Decapoda-Brachyura-Majoidea', 'Decapoda-Brachyura-Xanthoidea',\n",
       "       'Decapoda-Anomura-Lithoidea', 'Decapoda-Brachyura',\n",
       "       'Decapoda-Brachyura-cheiragonidae', 'Decapoda-Anomura-Porcellanidae',\n",
       "       'Decapoda-Anomura', 'Gastropoda', 'Euphausiidae',\n",
       "       'Euphausiidae-EUPHAUSIA-Nauplii', 'Euphausiidae-Nauplii',\n",
       "       'Euphausiidae-THYSANOESSA-Nauplii', 'Euphausiidae-EUPHAUSIA-Adult',\n",
       "       'Euphausiidae-THYSANOESSA-Adult', 'Euphausiidae-NEMATOSCELIS-Adult',\n",
       "       'Euphausiidae-EUPHAUSIA-Calyptopes',\n",
       "       'Euphausiidae-THYSANOESSA-Calyptopes', 'Euphausiidae-Calyptopes',\n",
       "       'Euphausiidae-EUPHAUSIA-Furcillia',\n",
       "       'Euphausiidae-THYSANOESSA-Furcillia', 'Euphausiidae-Furcillia',\n",
       "       'Chordata-Larvacea', 'Cnidaria-Scyphozoa',\n",
       "       'Cnidaria-Siphonophore-Calycophoran', 'Cnidaria-Siphonophore-Physonect',\n",
       "       'Cnidaria-Siphonophore', 'Chordata-Tunicata'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       0.011072\n",
       "1       0.020610\n",
       "2       0.000000\n",
       "3       0.011896\n",
       "4       0.021764\n",
       "          ...   \n",
       "1154    0.000000\n",
       "1155    0.000000\n",
       "1156    0.000598\n",
       "1157    0.000000\n",
       "1158    0.000000\n",
       "Name: Decapoda-Brachyura-Cancridae, Length: 1159, dtype: float64"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF['Decapoda-Brachyura-Cancridae']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "import netCDF4 as nc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ftemp=nc.Dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ftemp.variables.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ftemp.variables['e3t_0']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ftemp.variables['e3t_1d'][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "fdict={'ptrc_T':1,'grid_T':1}\n",
    "start_date = dt.datetime(2014,1,1)\n",
    "end_date = dt.datetime(2016,12,31)\n",
    "flen=1 # number of days per model output file. always 1 for 201905 and 201812 model runs\n",
    "namfmt='nowcast' # for 201905 and 201812 model runs, this should always be 'nowcast'\n",
    "# filemap is dictionary of the form variableName: fileType, where variableName is the name\n",
    "# of the variable you want to extract and fileType designates the type of \n",
    "# model output file it can be found in (usually ptrc_T for biology, grid_T for temperature and \n",
    "# salinity)\n",
    "filemap={'microzooplankton':'ptrc_T','mesozooplankton':'ptrc_T'}\n",
    "# fdict is a dictionary mappy file type to its time resolution. Here, 1 means hourly output\n",
    "# (1h file) and 24 means daily output (1d file). In certain runs, multiple time resolutions \n",
    "# are available\n",
    "fdict={'ptrc_T':1,'grid_T':1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "PATH= '/results2/SalishSea/nowcast-green.201905/'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Key', 'Station', 'Site Name', 'Basin', 'Sub Basin', 'Lat', 'Lon',\n",
       "       'Sample Date', 'Sample Year', 'Sample Month', 'Sample Time',\n",
       "       'Mesh Size', 'Diameter (cm)', 'Station Depth (m)', 'Max Tow Depth (m)',\n",
       "       'Min Tow Depth (m)', 'dtUTC', 'Amphipoda-Hyperiidea',\n",
       "       'Amphipoda-Cyphocarididae', 'Amphipoda-Calliopiidae',\n",
       "       'Amphipoda-Gammaridae', 'Amphipoda', 'Amphipoda-Corophiidae',\n",
       "       'Amphipoda-Caprellidae', 'Copepoda-Calanoida',\n",
       "       'Copepoda-Poecilostomatoida', 'Copepoda-Cyclopoida',\n",
       "       'Copepoda-Monstrilloida', 'Copepoda-Harpacticoida',\n",
       "       'Copepoda-Siphonostomatoida', 'Decapoda-Brachyura-Cancridae',\n",
       "       'Decapoda-Brachyura-Pinnotheridae', 'Decapoda-Anomura-Paguridae',\n",
       "       'Decapoda-Brachyura-Grapsoidea', 'Decapoda-Anomura-Galatheoidea',\n",
       "       'Decapoda-Brachyura-Majoidea', 'Decapoda-Brachyura-Xanthoidea',\n",
       "       'Decapoda-Anomura-Lithoidea', 'Decapoda-Brachyura',\n",
       "       'Decapoda-Brachyura-cheiragonidae', 'Decapoda-Anomura-Porcellanidae',\n",
       "       'Decapoda-Anomura', 'Gastropoda', 'Euphausiidae',\n",
       "       'Euphausiidae-EUPHAUSIA-Nauplii', 'Euphausiidae-Nauplii',\n",
       "       'Euphausiidae-THYSANOESSA-Nauplii', 'Euphausiidae-EUPHAUSIA-Adult',\n",
       "       'Euphausiidae-THYSANOESSA-Adult', 'Euphausiidae-NEMATOSCELIS-Adult',\n",
       "       'Euphausiidae-EUPHAUSIA-Calyptopes',\n",
       "       'Euphausiidae-THYSANOESSA-Calyptopes', 'Euphausiidae-Calyptopes',\n",
       "       'Euphausiidae-EUPHAUSIA-Furcillia',\n",
       "       'Euphausiidae-THYSANOESSA-Furcillia', 'Euphausiidae-Furcillia',\n",
       "       'Chordata-Larvacea', 'Cnidaria-Scyphozoa',\n",
       "       'Cnidaria-Siphonophore-Calycophoran', 'Cnidaria-Siphonophore-Physonect',\n",
       "       'Cnidaria-Siphonophore', 'Chordata-Tunicata'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomassDF.rename(columns={'Max Tow Depth (m)':'Z_lower','Min Tow Depth (m)':'Z_upper','Station Depth (m)':'Z'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define log transform function with slight shift to accommodate zero values\n",
    "def logt(x):\n",
    "  return np.log10(x+.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define inverse log transform with same shift\n",
    "def logt_inv(y):\n",
    "    return 10**y-.001"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "test3=np.array([0,0,0,0,1,3,5,10,15,1,1,1,3,1,2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1e-06 2.5942003176995434\n",
      "1e-05 2.5941913176995435\n",
      "0.0001 2.5941013176995433\n",
      "0.001 2.5932013176995437\n",
      "0.01 2.5842013176995438\n",
      "0.1 2.4942013176995435\n",
      "1 1.5942013176995435\n"
     ]
    }
   ],
   "source": [
    "for a in (1e-6,1e-5,1e-4,1e-3,1e-2,.1,1):\n",
    "    print(a,10**np.mean(np.log10(test3+1))-a)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomassDF['Year']=[ii.year for ii in biomassDF['dtUTC']]\n",
    "biomassDF['YD']=et.datetimeToYD(biomassDF['dtUTC'])\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "biomassDF['Amphipoda']=biomassDF['Amphipoda']/8.5\n",
    "biomassDF['Crabs']=biomassDF['Crabs']/8.5\n",
    "biomassDF['Krill-Adult Juvenile']=biomassDF['Krill-Adult Juvenile']/8.5\n",
    "biomassDF['Krill-Calyptopis']=biomassDF['Krill-Calyptopis']/8.5\n",
    "biomassDF['Krill-Furcilia']=biomassDF['Krill-Furcilia']/8.5\n",
    "biomassDF['Copepod']=biomassDF['Copepod']/8.5\n",
    "biomassDF['Larvacea']=biomassDF['Larvacea']/8.5\n",
    "biomassDF['Neocalanus']=(biomassDF['NEOCALANUS PLUMCHRUS']+biomassDF['NEOCALANUS CRISTATUS']+biomassDF['NEOCALANUS'])/8.5\n",
    "biomassDF['Calanus']=(biomassDF['CALANUS PACIFICUS']+biomassDF['CALANUS MARSHALLAE'])/8.5\n",
    "biomassDF['Metridia']=(biomassDF['METRIDIA PACIFICA']+biomassDF['METRIDIIDAE'])/8.5\n",
    "biomassDF['Eucalanus']=(biomassDF['EUCALANUS BUNGII']+biomassDF['EUCALANUS CALIFORNICUS']+biomassDF['EUCALANUS'])/8.5\n",
    "biomassDF['Calanoids']=(biomassDF['CALANOIDA']+biomassDF['NEOCALANUS PLUMCHRUS']+biomassDF['NEOCALANUS CRISTATUS']+biomassDF['NEOCALANUS']+biomassDF['CALANUS PACIFICUS']+biomassDF['CALANUS MARSHALLAE']+biomassDF['METRIDIA PACIFICA']+biomassDF['METRIDIIDAE']+biomassDF['EUCALANUS BUNGII']+biomassDF['EUCALANUS CALIFORNICUS']+biomassDF['EUCALANUS'])/8.5\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "#CN conversions for mid-level groups\n",
    "biomassDF['Amphipods']=(biomassDF['Amphipoda-Hyperiidea']+biomassDF['Amphipoda-Cyphocarididae']+biomassDF['Amphipoda-Calliopiidae']+biomassDF['Amphipoda-Gammaridae']+biomassDF['Amphipoda']+biomassDF['Amphipoda-Corophiidae']+biomassDF['Amphipoda-Caprellidae'])/8.5\n",
    "biomassDF['Crabs']=(biomassDF['Decapoda-Brachyura-Cancridae']+biomassDF['Decapoda-Brachyura-Pinnotheridae']+biomassDF['Decapoda-Anomura-Paguridae']+biomassDF['Decapoda-Brachyura-Grapsoidea']+biomassDF['Decapoda-Anomura-Galatheoidea']+biomassDF['Decapoda-Brachyura-Majoidea']+biomassDF['Decapoda-Brachyura-Xanthoidea']+biomassDF['Decapoda-Anomura-Lithoidea']+biomassDF['Decapoda-Brachyura']+biomassDF['Decapoda-Brachyura-cheiragonidae']+biomassDF['Decapoda-Anomura-Porcellanidae']+biomassDF['Decapoda-Anomura'])/8.5\n",
    "biomassDF['Euphausiids']=(biomassDF['Euphausiidae']+biomassDF['Euphausiidae-EUPHAUSIA-Nauplii']+biomassDF['Euphausiidae-Nauplii']+biomassDF['Euphausiidae-THYSANOESSA-Nauplii']+biomassDF['Euphausiidae-EUPHAUSIA-Adult']+biomassDF['Euphausiidae-THYSANOESSA-Adult']+biomassDF['Euphausiidae-NEMATOSCELIS-Adult']+biomassDF['Euphausiidae-EUPHAUSIA-Calyptopes']+biomassDF['Euphausiidae-THYSANOESSA-Calyptopes']+biomassDF['Euphausiidae-Calyptopes']+biomassDF['Euphausiidae-EUPHAUSIA-Furcillia']+biomassDF['Euphausiidae-THYSANOESSA-Furcillia']+biomassDF['Euphausiidae-Furcillia'])/8.5\n",
    "biomassDF['Calanoids']=biomassDF['Copepoda-Calanoida']/8.5\n",
    "biomassDF['NonCalanoids']=(biomassDF['Copepoda-Poecilostomatoida'])/8.5\n",
    "biomassDF['Gastropods']=biomassDF['Gastropoda']/8.5\n",
    "biomassDF['Larvaceans']=biomassDF['Chordata-Larvacea']/8.5\n",
    "biomassDF['HyperiidAmph']=biomassDF['Amphipoda-Hyperiidea']/8.5\n",
    "biomassDF['EuphausiidsJuv']=(biomassDF['Euphausiidae-EUPHAUSIA-Calyptopes']+biomassDF['Euphausiidae-THYSANOESSA-Calyptopes']+biomassDF['Euphausiidae-Calyptopes']+biomassDF['Euphausiidae-EUPHAUSIA-Furcillia']+biomassDF['Euphausiidae-THYSANOESSA-Furcillia']+biomassDF['Euphausiidae-Furcillia'])/8.5\n",
    "biomassDF['Jellies']=(biomassDF['Cnidaria-Scyphozoa']+biomassDF['Cnidaria-Siphonophore-Calycophoran']+biomassDF['Cnidaria-Siphonophore-Physonect']+biomassDF['Cnidaria-Siphonophore'])/8.5\n",
    "biomassDF['Tunicates']=biomassDF['Chordata-Tunicata']/8.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "biomassDF['Total']=(biomassDF['Amphipoda-Hyperiidea']+biomassDF['Amphipoda-Cyphocarididae']+biomassDF['Amphipoda-Calliopiidae']+biomassDF['Amphipoda-Gammaridae']+biomassDF['Amphipoda']+biomassDF['Amphipoda-Corophiidae']+biomassDF['Amphipoda-Caprellidae']+ \\\n",
    "                    biomassDF['Decapoda-Brachyura-Cancridae']+biomassDF['Decapoda-Brachyura-Pinnotheridae']+biomassDF['Decapoda-Anomura-Paguridae']+biomassDF['Decapoda-Brachyura-Grapsoidea']+biomassDF['Decapoda-Anomura-Galatheoidea']+biomassDF['Decapoda-Brachyura-Majoidea']+biomassDF['Decapoda-Brachyura-Xanthoidea']+biomassDF['Decapoda-Anomura-Lithoidea']+biomassDF['Decapoda-Brachyura']+biomassDF['Decapoda-Brachyura-cheiragonidae']+biomassDF['Decapoda-Anomura-Porcellanidae']+biomassDF['Decapoda-Anomura']+ \\\n",
    "                    biomassDF['Euphausiidae']+biomassDF['Euphausiidae-EUPHAUSIA-Nauplii']+biomassDF['Euphausiidae-Nauplii']+biomassDF['Euphausiidae-THYSANOESSA-Nauplii']+biomassDF['Euphausiidae-EUPHAUSIA-Adult']+biomassDF['Euphausiidae-THYSANOESSA-Adult']+biomassDF['Euphausiidae-NEMATOSCELIS-Adult']+biomassDF['Euphausiidae-EUPHAUSIA-Calyptopes']+biomassDF['Euphausiidae-THYSANOESSA-Calyptopes']+biomassDF['Euphausiidae-Calyptopes']+biomassDF['Euphausiidae-EUPHAUSIA-Furcillia']+biomassDF['Euphausiidae-THYSANOESSA-Furcillia']+biomassDF['Euphausiidae-Furcillia']+\\\n",
    "                    biomassDF['Copepoda-Calanoida']+biomassDF['Copepoda-Poecilostomatoida']+biomassDF['Gastropoda']+biomassDF['Chordata-Larvacea']+\\\n",
    "                    biomassDF['Cnidaria-Scyphozoa']+biomassDF['Cnidaria-Siphonophore-Calycophoran']+biomassDF['Cnidaria-Siphonophore-Physonect']+biomassDF['Cnidaria-Siphonophore'])/8.5\n",
    "            \n",
    "                    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "#+biomassDF['Copepoda-Cyclopoida']+biomassDF['Copepoda-Monstrilloida']+biomassDF['Copepoda-Harpacticoida']+biomassDF['Copepoda-Siphonostomatoida']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Key</th>\n",
       "      <th>Station</th>\n",
       "      <th>Site Name</th>\n",
       "      <th>Basin</th>\n",
       "      <th>Sub Basin</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Sample Date</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Sample Month</th>\n",
       "      <th>...</th>\n",
       "      <th>Euphausiids</th>\n",
       "      <th>Calanoids</th>\n",
       "      <th>NonCalanoids</th>\n",
       "      <th>Gastropods</th>\n",
       "      <th>Larvaceans</th>\n",
       "      <th>HyperiidAmph</th>\n",
       "      <th>EuphausiidsJuv</th>\n",
       "      <th>Jellies</th>\n",
       "      <th>Tunicates</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>010218ELIV1151</td>\n",
       "      <td>ELIV</td>\n",
       "      <td>Eliza Island</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>48.63795</td>\n",
       "      <td>-122.5694</td>\n",
       "      <td>2018-01-02</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.004292</td>\n",
       "      <td>0.375024</td>\n",
       "      <td>0.019583</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001192</td>\n",
       "      <td>0.004601</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.444270</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>010818SKETV1058</td>\n",
       "      <td>SKETV</td>\n",
       "      <td>South Ketron/Solo Point</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>47.15243</td>\n",
       "      <td>-122.6586</td>\n",
       "      <td>2018-01-08</td>\n",
       "      <td>2018</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.129670</td>\n",
       "      <td>0.026537</td>\n",
       "      <td>0.029498</td>\n",
       "      <td>0.014453</td>\n",
       "      <td>0.003771</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001408</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.252033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>011119ELIV1052</td>\n",
       "      <td>ELIV</td>\n",
       "      <td>Eliza Island</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>Bellingham Bay</td>\n",
       "      <td>48.63795</td>\n",
       "      <td>-122.5694</td>\n",
       "      <td>2019-01-11</td>\n",
       "      <td>2019</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.510291</td>\n",
       "      <td>0.017065</td>\n",
       "      <td>0.000204</td>\n",
       "      <td>0.000392</td>\n",
       "      <td>0.002408</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.618672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>011315CAMV1330</td>\n",
       "      <td>CAMV</td>\n",
       "      <td>Camano Head</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>48.05901</td>\n",
       "      <td>-122.3873</td>\n",
       "      <td>2015-01-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000656</td>\n",
       "      <td>0.326055</td>\n",
       "      <td>0.002908</td>\n",
       "      <td>0.056381</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.009314</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000880</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.436414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>011315MUKV1415</td>\n",
       "      <td>MUKV</td>\n",
       "      <td>Mukilteo</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>47.97166</td>\n",
       "      <td>-122.3222</td>\n",
       "      <td>2015-01-13</td>\n",
       "      <td>2015</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>0.008040</td>\n",
       "      <td>0.371331</td>\n",
       "      <td>0.015448</td>\n",
       "      <td>0.103455</td>\n",
       "      <td>0.001486</td>\n",
       "      <td>0.022127</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.675737</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1154</th>\n",
       "      <td>121917LSNT01V1000</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2017-12-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000462</td>\n",
       "      <td>0.188989</td>\n",
       "      <td>0.047149</td>\n",
       "      <td>0.026001</td>\n",
       "      <td>0.006724</td>\n",
       "      <td>0.012318</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.391030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1155</th>\n",
       "      <td>121917NSEX01V1224</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2017-12-19</td>\n",
       "      <td>2017</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000212</td>\n",
       "      <td>0.378846</td>\n",
       "      <td>0.095293</td>\n",
       "      <td>0.260524</td>\n",
       "      <td>0.021037</td>\n",
       "      <td>0.021455</td>\n",
       "      <td>0.000212</td>\n",
       "      <td>0.000779</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.873493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1156</th>\n",
       "      <td>121918TDBV1327</td>\n",
       "      <td>TDBV</td>\n",
       "      <td>Thorndyke Bay</td>\n",
       "      <td>Hood Canal</td>\n",
       "      <td>N Hood Canal</td>\n",
       "      <td>47.78297</td>\n",
       "      <td>-122.7330</td>\n",
       "      <td>2018-12-19</td>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000836</td>\n",
       "      <td>0.631083</td>\n",
       "      <td>0.036285</td>\n",
       "      <td>0.000163</td>\n",
       "      <td>0.003732</td>\n",
       "      <td>0.014347</td>\n",
       "      <td>0.000836</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.704923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1157</th>\n",
       "      <td>122116LSNT01V1057</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.340767</td>\n",
       "      <td>0.024335</td>\n",
       "      <td>0.069083</td>\n",
       "      <td>0.008240</td>\n",
       "      <td>0.019277</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001720</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.516747</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1158</th>\n",
       "      <td>122116NSEX01V1237</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0.006156</td>\n",
       "      <td>0.235630</td>\n",
       "      <td>0.017414</td>\n",
       "      <td>0.239483</td>\n",
       "      <td>0.015643</td>\n",
       "      <td>0.005761</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000630</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.660677</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1159 rows × 76 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Key  Station                Site Name           Basin  \\\n",
       "0        010218ELIV1151     ELIV             Eliza Island  Bellingham Bay   \n",
       "1       010818SKETV1058    SKETV  South Ketron/Solo Point     South Sound   \n",
       "2        011119ELIV1052     ELIV             Eliza Island  Bellingham Bay   \n",
       "3        011315CAMV1330     CAMV              Camano Head   Whidbey Basin   \n",
       "4        011315MUKV1415     MUKV                 Mukilteo   Whidbey Basin   \n",
       "...                 ...      ...                      ...             ...   \n",
       "1154  121917LSNT01V1000  LSNT01V           Point Williams   Central Basin   \n",
       "1155  121917NSEX01V1224  NSEX01V             East Passage   Central Basin   \n",
       "1156     121918TDBV1327     TDBV            Thorndyke Bay      Hood Canal   \n",
       "1157  122116LSNT01V1057  LSNT01V           Point Williams   Central Basin   \n",
       "1158  122116NSEX01V1237  NSEX01V             East Passage   Central Basin   \n",
       "\n",
       "            Sub Basin       Lat       Lon Sample Date  Sample Year  \\\n",
       "0      Bellingham Bay  48.63795 -122.5694  2018-01-02         2018   \n",
       "1         South Sound  47.15243 -122.6586  2018-01-08         2018   \n",
       "2      Bellingham Bay  48.63795 -122.5694  2019-01-11         2019   \n",
       "3     S Whidbey Basin  48.05901 -122.3873  2015-01-13         2015   \n",
       "4     S Whidbey Basin  47.97166 -122.3222  2015-01-13         2015   \n",
       "...               ...       ...       ...         ...          ...   \n",
       "1154  N Central Basin  47.53333 -122.4333  2017-12-19         2017   \n",
       "1155  S Central Basin  47.35862 -122.3871  2017-12-19         2017   \n",
       "1156     N Hood Canal  47.78297 -122.7330  2018-12-19         2018   \n",
       "1157  N Central Basin  47.53333 -122.4333  2016-12-21         2016   \n",
       "1158  S Central Basin  47.35862 -122.3871  2016-12-21         2016   \n",
       "\n",
       "      Sample Month  ... Euphausiids  Calanoids  NonCalanoids  Gastropods  \\\n",
       "0                1  ...    0.004292   0.375024      0.019583    0.000000   \n",
       "1                1  ...    0.000000   0.129670      0.026537    0.029498   \n",
       "2                1  ...    0.000000   0.510291      0.017065    0.000204   \n",
       "3                1  ...    0.000656   0.326055      0.002908    0.056381   \n",
       "4                1  ...    0.008040   0.371331      0.015448    0.103455   \n",
       "...            ...  ...         ...        ...           ...         ...   \n",
       "1154            12  ...    0.000462   0.188989      0.047149    0.026001   \n",
       "1155            12  ...    0.000212   0.378846      0.095293    0.260524   \n",
       "1156            12  ...    0.000836   0.631083      0.036285    0.000163   \n",
       "1157            12  ...    0.000000   0.340767      0.024335    0.069083   \n",
       "1158            12  ...    0.006156   0.235630      0.017414    0.239483   \n",
       "\n",
       "      Larvaceans  HyperiidAmph EuphausiidsJuv   Jellies  Tunicates     Total  \n",
       "0       0.001192      0.004601       0.000000  0.000000        0.0  0.444270  \n",
       "1       0.014453      0.003771       0.000000  0.001408        0.0  0.252033  \n",
       "2       0.000392      0.002408       0.000000  0.000000        0.0  0.618672  \n",
       "3       0.000000      0.009314       0.000000  0.000880        0.0  0.436414  \n",
       "4       0.001486      0.022127       0.000000  0.000000        0.0  0.675737  \n",
       "...          ...           ...            ...       ...        ...       ...  \n",
       "1154    0.006724      0.012318       0.000000  0.000000        0.0  0.391030  \n",
       "1155    0.021037      0.021455       0.000212  0.000779        0.0  0.873493  \n",
       "1156    0.003732      0.014347       0.000836  0.000000        0.0  0.704923  \n",
       "1157    0.008240      0.019277       0.000000  0.001720        0.0  0.516747  \n",
       "1158    0.015643      0.005761       0.000000  0.000630        0.0  0.660677  \n",
       "\n",
       "[1159 rows x 76 columns]"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Key', 'Station', 'Site Name', 'Basin', 'Sub Basin', 'Lat', 'Lon',\n",
       "       'Sample Date', 'Sample Year', 'Sample Month', 'Sample Time',\n",
       "       'Mesh Size', 'Diameter (cm)', 'Z', 'Z_lower', 'Z_upper', 'dtUTC',\n",
       "       'Amphipoda-Hyperiidea', 'Amphipoda-Cyphocarididae',\n",
       "       'Amphipoda-Calliopiidae', 'Amphipoda-Gammaridae', 'Amphipoda',\n",
       "       'Amphipoda-Corophiidae', 'Amphipoda-Caprellidae', 'Copepoda-Calanoida',\n",
       "       'Copepoda-Poecilostomatoida', 'Copepoda-Cyclopoida',\n",
       "       'Copepoda-Monstrilloida', 'Copepoda-Harpacticoida',\n",
       "       'Copepoda-Siphonostomatoida', 'Decapoda-Brachyura-Cancridae',\n",
       "       'Decapoda-Brachyura-Pinnotheridae', 'Decapoda-Anomura-Paguridae',\n",
       "       'Decapoda-Brachyura-Grapsoidea', 'Decapoda-Anomura-Galatheoidea',\n",
       "       'Decapoda-Brachyura-Majoidea', 'Decapoda-Brachyura-Xanthoidea',\n",
       "       'Decapoda-Anomura-Lithoidea', 'Decapoda-Brachyura',\n",
       "       'Decapoda-Brachyura-cheiragonidae', 'Decapoda-Anomura-Porcellanidae',\n",
       "       'Decapoda-Anomura', 'Gastropoda', 'Euphausiidae',\n",
       "       'Euphausiidae-EUPHAUSIA-Nauplii', 'Euphausiidae-Nauplii',\n",
       "       'Euphausiidae-THYSANOESSA-Nauplii', 'Euphausiidae-EUPHAUSIA-Adult',\n",
       "       'Euphausiidae-THYSANOESSA-Adult', 'Euphausiidae-NEMATOSCELIS-Adult',\n",
       "       'Euphausiidae-EUPHAUSIA-Calyptopes',\n",
       "       'Euphausiidae-THYSANOESSA-Calyptopes', 'Euphausiidae-Calyptopes',\n",
       "       'Euphausiidae-EUPHAUSIA-Furcillia',\n",
       "       'Euphausiidae-THYSANOESSA-Furcillia', 'Euphausiidae-Furcillia',\n",
       "       'Chordata-Larvacea', 'Cnidaria-Scyphozoa',\n",
       "       'Cnidaria-Siphonophore-Calycophoran', 'Cnidaria-Siphonophore-Physonect',\n",
       "       'Cnidaria-Siphonophore', 'Chordata-Tunicata', 'Year', 'YD', 'Amphipods',\n",
       "       'Crabs', 'Euphausiids', 'Calanoids', 'NonCalanoids', 'Gastropods',\n",
       "       'Larvaceans', 'HyperiidAmph', 'EuphausiidsJuv', 'Jellies', 'Tunicates',\n",
       "       'Total'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1000    10\n",
       "1001    10\n",
       "1002    10\n",
       "1003    10\n",
       "1004    10\n",
       "        ..\n",
       "1154    12\n",
       "1155    12\n",
       "1156    12\n",
       "1157    12\n",
       "1158    12\n",
       "Name: Sample Month, Length: 159, dtype: int64"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "biomassDF['Sample Month'][1000:1200]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "81587 data points\n",
      "Mean values per month by basin:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Mesh Size</th>\n",
       "      <th>Diameter (cm)</th>\n",
       "      <th>Z</th>\n",
       "      <th>Z_lower</th>\n",
       "      <th>Z_upper</th>\n",
       "      <th>Amphipoda-Hyperiidea</th>\n",
       "      <th>Amphipoda-Cyphocarididae</th>\n",
       "      <th>...</th>\n",
       "      <th>Euphausiids</th>\n",
       "      <th>Calanoids</th>\n",
       "      <th>NonCalanoids</th>\n",
       "      <th>Gastropods</th>\n",
       "      <th>Larvaceans</th>\n",
       "      <th>HyperiidAmph</th>\n",
       "      <th>EuphausiidsJuv</th>\n",
       "      <th>Jellies</th>\n",
       "      <th>Tunicates</th>\n",
       "      <th>Total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Basin</th>\n",
       "      <th>Sample Month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Admiralty Inlet</th>\n",
       "      <th>1</th>\n",
       "      <td>48.002730</td>\n",
       "      <td>-122.636000</td>\n",
       "      <td>2018.500000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>127.500000</td>\n",
       "      <td>112.500000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.068428</td>\n",
       "      <td>0.366462</td>\n",
       "      <td>...</td>\n",
       "      <td>0.129874</td>\n",
       "      <td>0.592499</td>\n",
       "      <td>0.009565</td>\n",
       "      <td>0.015369</td>\n",
       "      <td>0.002113</td>\n",
       "      <td>0.008050</td>\n",
       "      <td>0.000086</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.805615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>48.002730</td>\n",
       "      <td>-122.636000</td>\n",
       "      <td>2018.666667</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>127.333333</td>\n",
       "      <td>108.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.149914</td>\n",
       "      <td>0.123580</td>\n",
       "      <td>...</td>\n",
       "      <td>0.025843</td>\n",
       "      <td>0.443700</td>\n",
       "      <td>0.005510</td>\n",
       "      <td>0.032120</td>\n",
       "      <td>0.002341</td>\n",
       "      <td>0.017637</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.553720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>48.002730</td>\n",
       "      <td>-122.636000</td>\n",
       "      <td>2016.857143</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>123.285714</td>\n",
       "      <td>115.714286</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.063749</td>\n",
       "      <td>0.060303</td>\n",
       "      <td>...</td>\n",
       "      <td>0.058464</td>\n",
       "      <td>0.804039</td>\n",
       "      <td>0.017117</td>\n",
       "      <td>0.102259</td>\n",
       "      <td>0.068770</td>\n",
       "      <td>0.007500</td>\n",
       "      <td>0.037644</td>\n",
       "      <td>0.000468</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.464261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>48.002730</td>\n",
       "      <td>-122.636000</td>\n",
       "      <td>2017.000000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>115.125000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.091578</td>\n",
       "      <td>0.100046</td>\n",
       "      <td>...</td>\n",
       "      <td>0.116482</td>\n",
       "      <td>1.791811</td>\n",
       "      <td>0.022842</td>\n",
       "      <td>0.090444</td>\n",
       "      <td>0.059519</td>\n",
       "      <td>0.010774</td>\n",
       "      <td>0.114000</td>\n",
       "      <td>0.000260</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.414157</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>48.002730</td>\n",
       "      <td>-122.636000</td>\n",
       "      <td>2016.363636</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>123.063636</td>\n",
       "      <td>113.727273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.230561</td>\n",
       "      <td>0.106258</td>\n",
       "      <td>...</td>\n",
       "      <td>0.115418</td>\n",
       "      <td>2.721170</td>\n",
       "      <td>0.161041</td>\n",
       "      <td>0.117341</td>\n",
       "      <td>0.093221</td>\n",
       "      <td>0.144772</td>\n",
       "      <td>0.106803</td>\n",
       "      <td>0.000656</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>7.037134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">Whidbey Basin</th>\n",
       "      <th>8</th>\n",
       "      <td>48.105715</td>\n",
       "      <td>-122.417072</td>\n",
       "      <td>2016.827586</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>152.017241</td>\n",
       "      <td>144.827586</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.616324</td>\n",
       "      <td>5.889347</td>\n",
       "      <td>...</td>\n",
       "      <td>0.043426</td>\n",
       "      <td>1.217126</td>\n",
       "      <td>0.124648</td>\n",
       "      <td>0.330944</td>\n",
       "      <td>0.071258</td>\n",
       "      <td>0.072509</td>\n",
       "      <td>0.018164</td>\n",
       "      <td>0.028761</td>\n",
       "      <td>0.001283</td>\n",
       "      <td>2.620538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>48.167176</td>\n",
       "      <td>-122.456579</td>\n",
       "      <td>2016.666667</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>129.329167</td>\n",
       "      <td>120.583333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.242517</td>\n",
       "      <td>3.342096</td>\n",
       "      <td>...</td>\n",
       "      <td>0.063043</td>\n",
       "      <td>1.114140</td>\n",
       "      <td>0.120725</td>\n",
       "      <td>0.259831</td>\n",
       "      <td>0.104822</td>\n",
       "      <td>0.028531</td>\n",
       "      <td>0.015356</td>\n",
       "      <td>0.026761</td>\n",
       "      <td>0.002494</td>\n",
       "      <td>2.131343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>48.068845</td>\n",
       "      <td>-122.389336</td>\n",
       "      <td>2017.636364</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>168.581818</td>\n",
       "      <td>158.727273</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.133593</td>\n",
       "      <td>4.786002</td>\n",
       "      <td>...</td>\n",
       "      <td>0.009953</td>\n",
       "      <td>1.225630</td>\n",
       "      <td>0.106814</td>\n",
       "      <td>0.134034</td>\n",
       "      <td>0.045734</td>\n",
       "      <td>0.015717</td>\n",
       "      <td>0.002946</td>\n",
       "      <td>0.012287</td>\n",
       "      <td>0.000153</td>\n",
       "      <td>2.123320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>48.000777</td>\n",
       "      <td>-122.343900</td>\n",
       "      <td>2017.333333</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>190.666667</td>\n",
       "      <td>184.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.073500</td>\n",
       "      <td>3.057175</td>\n",
       "      <td>...</td>\n",
       "      <td>0.001545</td>\n",
       "      <td>0.811909</td>\n",
       "      <td>0.100365</td>\n",
       "      <td>0.072512</td>\n",
       "      <td>0.008817</td>\n",
       "      <td>0.008647</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.002816</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.375131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>48.029893</td>\n",
       "      <td>-122.365600</td>\n",
       "      <td>2016.500000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>184.666667</td>\n",
       "      <td>177.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.072564</td>\n",
       "      <td>2.801087</td>\n",
       "      <td>...</td>\n",
       "      <td>0.000043</td>\n",
       "      <td>1.021259</td>\n",
       "      <td>0.026652</td>\n",
       "      <td>0.068770</td>\n",
       "      <td>0.007935</td>\n",
       "      <td>0.008537</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.001053</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.467520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>81 rows × 67 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    Lat         Lon  Sample Year  Mesh Size  \\\n",
       "Basin           Sample Month                                                  \n",
       "Admiralty Inlet 1             48.002730 -122.636000  2018.500000      200.0   \n",
       "                2             48.002730 -122.636000  2018.666667      200.0   \n",
       "                3             48.002730 -122.636000  2016.857143      200.0   \n",
       "                4             48.002730 -122.636000  2017.000000      200.0   \n",
       "                5             48.002730 -122.636000  2016.363636      200.0   \n",
       "...                                 ...         ...          ...        ...   \n",
       "Whidbey Basin   8             48.105715 -122.417072  2016.827586      200.0   \n",
       "                9             48.167176 -122.456579  2016.666667      200.0   \n",
       "                10            48.068845 -122.389336  2017.636364      200.0   \n",
       "                11            48.000777 -122.343900  2017.333333      200.0   \n",
       "                12            48.029893 -122.365600  2016.500000      200.0   \n",
       "\n",
       "                              Diameter (cm)           Z     Z_lower  Z_upper  \\\n",
       "Basin           Sample Month                                                   \n",
       "Admiralty Inlet 1                      60.0  127.500000  112.500000      0.0   \n",
       "                2                      60.0  127.333333  108.000000      0.0   \n",
       "                3                      60.0  123.285714  115.714286      0.0   \n",
       "                4                      60.0  125.000000  115.125000      0.0   \n",
       "                5                      60.0  123.063636  113.727273      0.0   \n",
       "...                                     ...         ...         ...      ...   \n",
       "Whidbey Basin   8                      60.0  152.017241  144.827586      0.0   \n",
       "                9                      60.0  129.329167  120.583333      0.0   \n",
       "                10                     60.0  168.581818  158.727273      0.0   \n",
       "                11                     60.0  190.666667  184.000000      0.0   \n",
       "                12                     60.0  184.666667  177.666667      0.0   \n",
       "\n",
       "                              Amphipoda-Hyperiidea  Amphipoda-Cyphocarididae  \\\n",
       "Basin           Sample Month                                                   \n",
       "Admiralty Inlet 1                         0.068428                  0.366462   \n",
       "                2                         0.149914                  0.123580   \n",
       "                3                         0.063749                  0.060303   \n",
       "                4                         0.091578                  0.100046   \n",
       "                5                         1.230561                  0.106258   \n",
       "...                                            ...                       ...   \n",
       "Whidbey Basin   8                         0.616324                  5.889347   \n",
       "                9                         0.242517                  3.342096   \n",
       "                10                        0.133593                  4.786002   \n",
       "                11                        0.073500                  3.057175   \n",
       "                12                        0.072564                  2.801087   \n",
       "\n",
       "                              ...  Euphausiids  Calanoids  NonCalanoids  \\\n",
       "Basin           Sample Month  ...                                         \n",
       "Admiralty Inlet 1             ...     0.129874   0.592499      0.009565   \n",
       "                2             ...     0.025843   0.443700      0.005510   \n",
       "                3             ...     0.058464   0.804039      0.017117   \n",
       "                4             ...     0.116482   1.791811      0.022842   \n",
       "                5             ...     0.115418   2.721170      0.161041   \n",
       "...                           ...          ...        ...           ...   \n",
       "Whidbey Basin   8             ...     0.043426   1.217126      0.124648   \n",
       "                9             ...     0.063043   1.114140      0.120725   \n",
       "                10            ...     0.009953   1.225630      0.106814   \n",
       "                11            ...     0.001545   0.811909      0.100365   \n",
       "                12            ...     0.000043   1.021259      0.026652   \n",
       "\n",
       "                              Gastropods  Larvaceans  HyperiidAmph  \\\n",
       "Basin           Sample Month                                         \n",
       "Admiralty Inlet 1               0.015369    0.002113      0.008050   \n",
       "                2               0.032120    0.002341      0.017637   \n",
       "                3               0.102259    0.068770      0.007500   \n",
       "                4               0.090444    0.059519      0.010774   \n",
       "                5               0.117341    0.093221      0.144772   \n",
       "...                                  ...         ...           ...   \n",
       "Whidbey Basin   8               0.330944    0.071258      0.072509   \n",
       "                9               0.259831    0.104822      0.028531   \n",
       "                10              0.134034    0.045734      0.015717   \n",
       "                11              0.072512    0.008817      0.008647   \n",
       "                12              0.068770    0.007935      0.008537   \n",
       "\n",
       "                              EuphausiidsJuv   Jellies  Tunicates     Total  \n",
       "Basin           Sample Month                                                 \n",
       "Admiralty Inlet 1                   0.000086  0.000000   0.000000  0.805615  \n",
       "                2                   0.000000  0.000000   0.000000  0.553720  \n",
       "                3                   0.037644  0.000468   0.000000  1.464261  \n",
       "                4                   0.114000  0.000260   0.000000  2.414157  \n",
       "                5                   0.106803  0.000656   0.000000  7.037134  \n",
       "...                                      ...       ...        ...       ...  \n",
       "Whidbey Basin   8                   0.018164  0.028761   0.001283  2.620538  \n",
       "                9                   0.015356  0.026761   0.002494  2.131343  \n",
       "                10                  0.002946  0.012287   0.000153  2.123320  \n",
       "                11                  0.000000  0.002816   0.000000  1.375131  \n",
       "                12                  0.000000  0.001053   0.000000  1.467520  \n",
       "\n",
       "[81 rows x 67 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(len(df),'data points')\n",
    "print('Mean values per month by basin:')\n",
    "biomassDF.groupby(['Basin','Sample Month']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "monthsFmt = mdates.DateFormatter('%b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#recreated groups below after model values were included in dataframe\n",
    "monthCala=biomassDF.groupby(['Sample Month', 'Calanoids'], as_index=False).mean()\n",
    "monthEuph=biomassDF.groupby(['Sample Month', 'Euphausiids'], as_index=False).mean()\n",
    "monthAmph=biomassDF.groupby(['Sample Month', 'Amphipods'], as_index=False).mean()\n",
    "monthCrab=biomassDF.groupby(['Sample Month', 'Crabs'], as_index=False).mean()\n",
    "monthNonCala=biomassDF.groupby(['Sample Month', 'NonCalanoids'], as_index=False).mean()\n",
    "monthLarv=biomassDF.groupby(['Sample Month', 'Larvaceans'], as_index=False).mean()\n",
    "monthGast=biomassDF.groupby(['Sample Month', 'Gastropods'], as_index=False).mean()\n",
    "monthJellies=biomassDF.groupby(['Sample Month', 'Jellies'], as_index=False).mean()\n",
    "monthTotal=biomassDF.groupby(['Sample Month', 'Total'], as_index=False).mean()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#recreated figures below after model was included in dataframe \n",
    "fig,ax=plt.subplots(1,4,figsize=(20,5))\n",
    "ax[0].plot(monthCala['Sample Month'],monthCala['Calanoids'],'r.')\n",
    "ax[1].plot(monthEuph['Sample Month'],monthEuph['Euphausiids'],'r.')\n",
    "ax[2].plot(monthAmph['Sample Month'],monthAmph['Amphipods'],'r.')\n",
    "ax[3].plot(monthCrab['Sample Month'],monthCrab['Crabs'],'r.')\n",
    "ax[0].set_title('Calanoid Seasonal Cycle')\n",
    "ax[1].set_title('Euphausiid Seasonal Cycle')\n",
    "ax[2].set_title('Amphipod Seasonal Cycle')\n",
    "ax[3].set_title('Decapod Seasonal Cycle')\n",
    "ax[0].set_xlim(0,13)\n",
    "ax[1].set_xlim(0,13)\n",
    "ax[2].set_xlim(0,13)\n",
    "ax[3].set_xlim(0,13)\n",
    "ax[0].set_ylim(0,10)\n",
    "ax[1].set_ylim(0,10)\n",
    "ax[2].set_ylim(0,10)\n",
    "ax[3].set_ylim(0,10)\n",
    "\n",
    "fig,ax=plt.subplots(1,4,figsize=(20,5))\n",
    "ax[0].plot(monthNonCala['Sample Month'],monthNonCala['NonCalanoids'],'r.')\n",
    "ax[1].plot(monthLarv['Sample Month'],monthLarv['Larvaceans'],'r.')\n",
    "ax[2].plot(monthGast['Sample Month'],monthGast['Gastropods'],'r.')\n",
    "ax[3].plot(monthJellies['Sample Month'],monthJellies['Jellies'],'r.')\n",
    "ax[0].set_title('Non Calanoid Seasonal Cycle')\n",
    "ax[1].set_title('Larvacean Seasonal Cycle')\n",
    "ax[2].set_title('Gastropod Seasonal Cycle')\n",
    "ax[3].set_title('Jellies Seasonal Cycle')\n",
    "ax[0].set_xlim(0,13)\n",
    "ax[1].set_xlim(0,13)\n",
    "ax[2].set_xlim(0,13)\n",
    "ax[3].set_xlim(0,13)\n",
    "ax[0].set_ylim(0,10)\n",
    "ax[1].set_ylim(0,10)\n",
    "ax[2].set_ylim(0,10)\n",
    "ax[3].set_ylim(0,10)"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#recreated figures below after model was included in dataframe \n",
    "fig,ax=plt.subplots(1,1,figsize=(12,5))\n",
    "ax.plot(monthTotal['Sample Month'],monthTotal['Total'],'.')\n",
    "ax.set_title('Total Zooplankton Seasonal Cycle')\n",
    "ax.set_xlim(0,13)\n",
    "ax.set_ylim(0,20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-03-25 17:35:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-03-25 17:35:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-04-09 16:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-04-09 16:25:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-04-09 18:38:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-04-09 18:38:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-04-22 18:57:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-04-22 18:57:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-04-22 21:20:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-04-22 21:20:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=20, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-04-25 19:15:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=20, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-04-25 19:15:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-05-01 01:10:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-05-01 01:10:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-05-07 17:05:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-05-07 17:05:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-05-14 19:20:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-05-14 19:20:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-05-16 02:00:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-05-16 02:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-05-16 19:12:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-05-16 19:12:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-05-19 16:35:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-05-19 16:35:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-05-22 21:40:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-05-22 21:40:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-05-29 22:03:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-05-29 22:03:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-06-01 02:45:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-06-01 02:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-06-04 16:26:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-06-04 16:26:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-06-06 20:15:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-06-06 20:15:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-06-13 01:25:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-06-13 01:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-06-17 17:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-06-17 17:25:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-06-19 17:40:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-06-19 17:40:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-06-19 20:40:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-06-19 20:40:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-06-24 18:47:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-06-24 18:47:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-06-25 22:03:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-06-25 22:03:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=24, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-06-27 02:30:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=24, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-06-27 02:30:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-07-07 17:05:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-07-07 17:05:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-07-08 20:55:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-07-08 20:55:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-07-14 18:36:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-07-14 18:36:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2014-07-17 18:15:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2014-07-17 18:15:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=23, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-07-18 18:30:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=23, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-07-18 18:30:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-07-21 16:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-07-21 16:45:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-07-25 19:52:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-07-25 19:52:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-07-27 00:55:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-07-27 00:55:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=27, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-07-29 19:25:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=27, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-07-29 19:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-08-04 18:40:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-08-04 18:40:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-08-15 01:15:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-08-15 01:15:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-08-15 21:11:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-08-15 21:11:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-08-18 16:30:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-08-18 16:30:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2014-08-18 18:05:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2014-08-18 18:05:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-08-19 18:15:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-08-19 18:15:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=24, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-08-20 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=24, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-08-20 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-08-29 19:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-08-29 19:00:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-08-31 00:40:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-08-31 00:40:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=29, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-09-04 19:17:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=29, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-09-04 19:17:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-09-08 16:40:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-09-08 16:40:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-09-12 01:16:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2014-09-12 01:16:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-09-12 19:50:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-09-12 19:50:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-09-18 17:25:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2014-09-18 17:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-09-22 16:50:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-09-22 16:50:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=28, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-09-25 19:12:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=28, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2014-09-25 19:12:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-10-06 16:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-10-06 16:45:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-10-08 20:06:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2014-10-08 20:06:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-10-20 16:40:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-10-20 16:40:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=29, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2014-10-30 16:49:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=29, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2014-10-30 16:49:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-11-03 18:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-11-03 18:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-11-17 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-11-17 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2014-12-02 19:11:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2014-12-02 19:11:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2014-12-02 22:40:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2014-12-02 22:40:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-12-15 17:47:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2014-12-15 17:47:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-01-13 21:30:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-01-13 21:30:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-01-13 22:15:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-01-13 22:15:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-01-20 17:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-01-20 17:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-02-02 16:52:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-02-02 16:52:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-02-17 17:55:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-02-17 17:55:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-03-02 18:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-03-02 18:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-03-10 20:29:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-03-10 20:29:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-03-18 18:20:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-03-18 18:20:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-03-20 18:35:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-03-20 18:35:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-03-20 19:46:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-03-20 19:46:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-03-23 16:30:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-03-23 16:30:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-03-27 20:15:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-03-27 20:15:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-04-02 18:27:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-04-02 18:27:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-04-04 23:35:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-04-04 23:35:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-04-06 16:20:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-04-06 16:20:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-04-07 18:58:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-04-07 18:58:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-04-07 20:03:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-04-07 20:03:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-04-15 19:49:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-04-15 19:49:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-04-15 20:47:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-04-15 20:47:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-04-20 17:42:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-04-20 17:42:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=24, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-04-21 20:25:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=24, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-04-21 20:25:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-04-29 21:59:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-04-29 21:59:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-05-04 16:41:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-05-04 16:41:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-05-06 19:00:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-05-06 19:00:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-05-06 20:05:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-05-06 20:05:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-05-11 23:01:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-05-11 23:01:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-05-13 18:59:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-05-13 18:59:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-05-14 20:17:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-05-14 20:17:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-05-17 01:05:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-05-17 01:05:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-05-18 17:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-05-18 17:00:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-05-21 18:39:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-05-21 18:39:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-05-21 19:40:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-05-21 19:40:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-05-26 18:10:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-05-26 18:10:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=21, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-05-27 22:49:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=21, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-05-27 22:49:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-05-28 20:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-05-28 20:00:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-05-31 02:30:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-05-31 02:30:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-06-02 16:08:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-06-02 16:08:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-06-08 18:03:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-06-08 18:03:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-06-08 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-06-08 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-06-10 18:22:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-06-10 18:22:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-06-14 02:25:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-06-14 02:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-06-16 16:35:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-06-16 16:35:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-06-17 21:05:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-06-17 21:05:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-06-18 19:53:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-06-18 19:53:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-06-23 17:15:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-06-23 17:15:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-06-23 19:19:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-06-23 19:19:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-06-25 18:04:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-06-25 18:04:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-06-26 18:32:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-06-26 18:32:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-06-28 01:10:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-06-28 01:10:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-07-01 20:09:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-07-01 20:09:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-07-01 20:34:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-07-01 20:34:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-07-06 17:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-07-06 17:00:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-07-09 17:59:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-07-09 17:59:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-07-09 18:42:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-07-09 18:42:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-07-09 19:49:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-07-09 19:49:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=24, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-07-13 02:00:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=24, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-07-13 02:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-07-13 20:37:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-07-13 20:37:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-07-15 20:32:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-07-15 20:32:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-07-20 16:27:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-07-20 16:27:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-07-22 17:34:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-07-22 17:34:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2015-07-23 19:05:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2015-07-23 19:05:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=23, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-07-27 19:12:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=23, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-07-27 19:12:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-07-30 18:53:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-07-30 18:53:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-07-30 19:58:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-07-30 19:58:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-08-01 03:00:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-08-01 03:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-08-03 19:18:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-08-03 19:18:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-08-04 17:57:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-08-04 17:57:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-08-04 20:47:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-08-04 20:47:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-08-06 18:18:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-08-06 18:18:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-08-13 18:21:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-08-13 18:21:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-08-13 19:21:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-08-13 19:21:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-08-16 01:55:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-08-16 01:55:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-08-17 21:47:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-08-17 21:47:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-08-18 18:03:00\n",
      "Warning: lower limit is not an ocean value:  i=126, j=22, k_upper=0, k_lower=23, k_seafloor=23 Lon=-122.8307, Lat=47.18327, dtUTC=2015-08-18 18:03:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-08-20 20:32:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-08-20 20:32:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-08-24 18:10:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-08-24 18:10:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=29, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-08-26 18:16:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=29, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-08-26 18:16:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-08-26 18:18:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-08-26 18:18:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-08-26 19:55:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-08-26 19:55:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-09-01 00:40:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=23, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2015-09-01 00:40:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-09-08 16:22:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-09-08 16:22:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-09-09 19:00:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-09-09 19:00:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-09-09 21:44:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-09-09 21:44:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-09-10 18:50:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-09-10 18:50:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-09-10 20:25:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-09-10 20:25:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-09-14 16:23:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-09-14 16:23:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-09-21 16:40:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-09-21 16:40:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2015-09-21 18:05:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2015-09-21 18:05:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-09-22 17:49:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2015-09-22 17:49:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-09-24 19:15:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2015-09-24 19:15:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=29, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-09-30 18:27:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=29, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2015-09-30 18:27:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-09-30 20:51:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=29, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2015-09-30 20:51:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-10-02 20:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-10-02 20:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-10-05 16:42:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-10-05 16:42:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-10-19 16:14:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-10-19 16:14:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-10-21 20:04:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2015-10-21 20:04:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-11-02 17:10:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-11-02 17:10:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-11-19 16:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-11-19 16:25:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-12-14 17:22:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2015-12-14 17:22:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-01-19 17:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-01-19 17:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-02-01 17:15:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-02-01 17:15:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-02-16 17:02:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-02-16 17:02:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-03-09 17:22:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-03-09 17:22:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-03-15 20:53:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-03-15 20:53:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-03-15 21:30:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-03-15 21:30:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-03-18 16:18:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-03-18 16:18:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-03-21 16:54:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-03-21 16:54:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-03-22 20:49:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-03-22 20:49:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-03-29 17:16:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-03-29 17:16:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-03-29 18:44:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-03-29 18:44:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-03-30 22:55:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-03-30 22:55:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-04-06 16:09:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-04-06 16:09:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-04-06 18:29:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-04-06 18:29:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-04-07 00:17:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-04-07 00:17:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-04-18 16:36:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-04-18 16:36:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-04-18 17:51:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-04-18 17:51:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-04-18 18:55:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-04-18 18:55:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-04-20 20:07:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-04-20 20:07:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=20, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-04-21 00:37:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=20, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-04-21 00:37:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-05-02 15:57:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-05-02 15:57:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-05-03 16:12:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-05-03 16:12:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-05-04 17:37:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-05-04 17:37:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-05-07 01:44:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-05-07 01:44:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-05-11 15:12:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-05-11 15:12:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-05-16 15:57:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-05-16 15:57:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-05-19 20:10:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-05-19 20:10:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-05-21 02:04:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-05-21 02:04:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-05-25 18:02:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-05-25 18:02:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-05-25 19:02:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-05-25 19:02:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-05-27 15:24:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-05-27 15:24:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-06-02 21:00:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-06-02 21:00:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=20, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-06-05 01:02:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=20, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-06-05 01:02:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-06-06 16:13:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-06-06 16:13:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-06-09 19:34:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-06-09 19:34:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-06-13 18:31:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-06-13 18:31:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-06-15 22:36:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-06-15 22:36:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-06-18 01:56:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-06-18 01:56:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-06-20 16:45:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-06-20 16:45:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-06-29 17:25:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-06-29 17:25:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-06-29 18:46:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-06-29 18:46:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2016-06-29 21:34:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2016-06-29 21:34:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-06-30 19:44:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-06-30 19:44:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-07-01 20:39:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-07-01 20:39:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-07-04 02:41:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-07-04 02:41:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-07-05 15:44:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-07-05 15:44:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-07-14 17:28:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-07-14 17:28:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-07-14 18:37:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-07-14 18:37:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-07-14 20:44:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-07-14 20:44:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2016-07-14 20:55:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2016-07-14 20:55:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-07-15 20:05:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-07-15 20:05:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-07-18 01:54:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-07-18 01:54:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-07-18 16:05:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-07-18 16:05:00\n",
      "Warning: lower limit is not an ocean value:  i=118, j=70, k_upper=0, k_lower=23, k_seafloor=23 Lon=-123.0249, Lat=47.3562, dtUTC=2016-07-21 20:11:00\n",
      "Warning: lower limit is not an ocean value:  i=118, j=70, k_upper=0, k_lower=23, k_seafloor=23 Lon=-123.0249, Lat=47.3562, dtUTC=2016-07-21 20:11:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-07-27 21:08:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-07-27 21:08:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-08-01 02:23:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-08-01 02:23:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-08-01 16:02:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-08-01 16:02:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-08-03 20:27:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-08-03 20:27:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-08-09 17:28:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-08-09 17:28:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-08-10 18:30:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-08-10 18:30:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-08-10 19:31:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-08-10 19:31:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-08-15 15:46:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-08-15 15:46:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=25, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-08-19 02:46:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=25, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-08-19 02:46:00\n",
      "Warning: lower limit is not an ocean value:  i=284, j=262, k_upper=0, k_lower=25, k_seafloor=24 Lon=-122.7929, Lat=48.43548, dtUTC=2016-08-19 03:21:00\n",
      "Warning: lower limit is not an ocean value:  i=284, j=262, k_upper=0, k_lower=25, k_seafloor=24 Lon=-122.7929, Lat=48.43548, dtUTC=2016-08-19 03:21:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-08-25 17:49:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-08-25 17:49:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-08-26 18:23:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-08-26 18:23:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-08-31 17:50:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-08-31 17:50:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-08-31 18:51:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-08-31 18:51:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-09-04 01:46:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-09-04 01:46:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-09-06 15:33:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-09-06 15:33:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-09-08 18:41:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-09-08 18:41:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-09-09 18:12:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-09-09 18:12:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-09-18 21:38:00\n",
      "Warning: lower limit is not an ocean value:  i=282, j=263, k_upper=0, k_lower=21, k_seafloor=18 Lon=-122.8037, Lat=48.43457, dtUTC=2016-09-18 21:38:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-09-19 15:48:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-09-19 15:48:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2016-09-20 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=298, j=210, k_upper=0, k_lower=25, k_seafloor=25 Lon=-122.5442, Lat=48.25673, dtUTC=2016-09-20 18:45:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2016-09-22 16:30:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=22, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2016-09-22 16:30:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-09-22 17:31:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-09-22 17:31:00\n",
      "Warning: lower limit is not an ocean value:  i=118, j=70, k_upper=0, k_lower=23, k_seafloor=23 Lon=-123.0249, Lat=47.3562, dtUTC=2016-09-26 20:59:00\n",
      "Warning: lower limit is not an ocean value:  i=118, j=70, k_upper=0, k_lower=23, k_seafloor=23 Lon=-123.0249, Lat=47.3562, dtUTC=2016-09-26 20:59:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-09-28 18:31:00\n",
      "Warning: lower limit is not an ocean value:  i=296, j=140, k_upper=0, k_lower=30, k_seafloor=29 Lon=-122.3222, Lat=47.97166, dtUTC=2016-09-28 18:31:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-09-28 19:21:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-09-28 19:21:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-09-29 20:56:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-09-29 20:56:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-10-03 16:13:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-10-03 16:13:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-10-11 22:37:00\n",
      "Warning: lower limit is not an ocean value:  i=342, j=285, k_upper=0, k_lower=27, k_seafloor=26 Lon=-122.5694, Lat=48.63795, dtUTC=2016-10-11 22:37:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-10-17 15:47:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-10-17 15:47:00\n",
      "Warning: lower limit is not an ocean value:  i=118, j=70, k_upper=0, k_lower=23, k_seafloor=23 Lon=-123.0249, Lat=47.3562, dtUTC=2016-10-20 21:05:00\n",
      "Warning: lower limit is not an ocean value:  i=118, j=70, k_upper=0, k_lower=23, k_seafloor=23 Lon=-123.0249, Lat=47.3562, dtUTC=2016-10-20 21:05:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-10-21 18:34:00\n",
      "Warning: lower limit is not an ocean value:  i=213, j=132, k_upper=0, k_lower=26, k_seafloor=26 Lon=-122.733, Lat=47.78297, dtUTC=2016-10-21 18:34:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=23, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2016-10-27 00:07:00\n",
      "Warning: lower limit is not an ocean value:  i=312, j=241, k_upper=0, k_lower=23, k_seafloor=20 Lon=-122.5783, Lat=48.40622, dtUTC=2016-10-27 00:07:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-11-07 19:10:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-11-07 19:10:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-11-21 16:41:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-11-21 16:41:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-12-03 20:00:00\n",
      "Warning: lower limit is not an ocean value:  i=297, j=161, k_upper=0, k_lower=30, k_seafloor=26 Lon=-122.3873, Lat=48.05901, dtUTC=2016-12-03 20:00:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-12-19 21:33:00\n",
      "Warning: lower limit is not an ocean value:  i=252, j=103, k_upper=0, k_lower=30, k_seafloor=30 Lon=-122.4282, Lat=47.74396, dtUTC=2016-12-19 21:33:00\n"
     ]
    }
   ],
   "source": [
    "data=et.matchData(biomassDF,filemap,fdict,start_date,end_date,'nowcast',PATH,1,quiet=False,method='vertNet');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "##L10 for mid-level groups\n",
    "data['L10Amphipods']=logt(data['Amphipoda'])\n",
    "data['L10Euphausiids']=logt(data['Euphausiids'])\n",
    "data['L10Crabs']=logt(data['Crabs'])\n",
    "data['L10Calanoids']=logt(data['Calanoids'])\n",
    "data['L10Gastropods']=logt(data['Gastropods'])\n",
    "data['L10Larvaceans']=logt(data['Larvaceans'])\n",
    "data['L10EuphausiidsJuv']=logt(data['EuphausiidsJuv'])\n",
    "data['L10HyperiidAmph']=logt(data['HyperiidAmph'])\n",
    "data['L10NonCalanoids']=logt(data['NonCalanoids'])\n",
    "data['L10Jellies']=logt(data['Jellies'])\n",
    "data['L10Tunicates']=logt(data['Tunicates'])\n",
    "data['L10Total']=logt(data['Total'])\n",
    "\n",
    "data['L10mod_microzooplankton']=logt(data['mod_microzooplankton'])\n",
    "data['L10mod_mesozooplankton']=logt(data['mod_mesozooplankton'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "##L10 for mid-level groups adults only"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "data['L10Amphipoda']=logt(data['Amphipoda'])\n",
    "data['L10Crabs']=logt(data['Crabs'])\n",
    "data['L10Krill-Adult Juvenile']=logt(data['Krill-Adult Juvenile'])\n",
    "data['L10Krill-Calyptopis']=logt(data['Krill-Calyptopis'])\n",
    "data['L10Krill-Furcilia']=logt(data['Krill-Furcilia'])\n",
    "data['L10Copepod']=logt(data['Copepod'])\n",
    "data['L10Larvacea']=logt(data['Larvacea'])\n",
    "data['L10Eucalanus']=logt(data['Eucalanus'])\n",
    "data['L10Neocalanus']=logt(data['Neocalanus'])\n",
    "data['L10Metridia']=logt(data['Metridia'])\n",
    "data['L10Calanus']=logt(data['Calanus'])\n",
    "data['L10Calanoids']=logt(data['Calanoids'])\n",
    "data['L10mod_microzooplankton']=logt(data['mod_microzooplankton'])\n",
    "data['L10mod_mesozooplankton']=logt(data['mod_mesozooplankton'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Key</th>\n",
       "      <th>Station</th>\n",
       "      <th>Site Name</th>\n",
       "      <th>Basin</th>\n",
       "      <th>Sub Basin</th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Sample Date</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Sample Month</th>\n",
       "      <th>...</th>\n",
       "      <th>L10Gastropods</th>\n",
       "      <th>L10Larvaceans</th>\n",
       "      <th>L10EuphausiidsJuv</th>\n",
       "      <th>L10HyperiidAmph</th>\n",
       "      <th>L10NonCalanoids</th>\n",
       "      <th>L10Jellies</th>\n",
       "      <th>L10Tunicates</th>\n",
       "      <th>L10Total</th>\n",
       "      <th>L10mod_microzooplankton</th>\n",
       "      <th>L10mod_mesozooplankton</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>032514DANAV1035</td>\n",
       "      <td>DANAV</td>\n",
       "      <td>Dana Passage</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>47.18327</td>\n",
       "      <td>-122.8307</td>\n",
       "      <td>2014-03-25</td>\n",
       "      <td>2014</td>\n",
       "      <td>3</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.963590</td>\n",
       "      <td>-1.759306</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-1.813082</td>\n",
       "      <td>-1.927517</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.938520</td>\n",
       "      <td>-0.636064</td>\n",
       "      <td>-0.203705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>040114sketv1001</td>\n",
       "      <td>SKETV</td>\n",
       "      <td>South Ketron/Solo Point</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>South Sound</td>\n",
       "      <td>47.15243</td>\n",
       "      <td>-122.6586</td>\n",
       "      <td>2014-04-01</td>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.390759</td>\n",
       "      <td>-1.454509</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-2.419121</td>\n",
       "      <td>-1.236035</td>\n",
       "      <td>-1.954179</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.474971</td>\n",
       "      <td>-0.553034</td>\n",
       "      <td>-0.345361</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>040414ADIV1300</td>\n",
       "      <td>ADIV</td>\n",
       "      <td>Admiralty Inlet</td>\n",
       "      <td>Admiralty Inlet</td>\n",
       "      <td>Admiralty Inlet</td>\n",
       "      <td>48.00273</td>\n",
       "      <td>-122.6360</td>\n",
       "      <td>2014-04-04</td>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.768568</td>\n",
       "      <td>-1.338911</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-2.288450</td>\n",
       "      <td>-2.167170</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>0.143507</td>\n",
       "      <td>-0.334718</td>\n",
       "      <td>-0.191273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>040914ksbp010925</td>\n",
       "      <td>KSBP01V</td>\n",
       "      <td>Point Jefferson</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.74396</td>\n",
       "      <td>-122.4282</td>\n",
       "      <td>2014-04-09</td>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.867468</td>\n",
       "      <td>-0.846542</td>\n",
       "      <td>-2.548761</td>\n",
       "      <td>-1.611418</td>\n",
       "      <td>-1.625231</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-2.248787</td>\n",
       "      <td>-0.101888</td>\n",
       "      <td>-0.484170</td>\n",
       "      <td>-0.286597</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>040914lsnt01v1055</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2014-04-09</td>\n",
       "      <td>2014</td>\n",
       "      <td>4</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.798123</td>\n",
       "      <td>-0.933799</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-2.920209</td>\n",
       "      <td>-1.637045</td>\n",
       "      <td>-2.677876</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.336873</td>\n",
       "      <td>-0.793377</td>\n",
       "      <td>-0.527014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>481</th>\n",
       "      <td>112216NSEX01V1304</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2016-11-22</td>\n",
       "      <td>2016</td>\n",
       "      <td>11</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.451538</td>\n",
       "      <td>-1.187045</td>\n",
       "      <td>-2.722048</td>\n",
       "      <td>-1.354277</td>\n",
       "      <td>-0.996189</td>\n",
       "      <td>-2.496160</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.035765</td>\n",
       "      <td>-1.384651</td>\n",
       "      <td>-0.436282</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>482</th>\n",
       "      <td>120316CAMV1200</td>\n",
       "      <td>CAMV</td>\n",
       "      <td>Camano Head</td>\n",
       "      <td>Whidbey Basin</td>\n",
       "      <td>S Whidbey Basin</td>\n",
       "      <td>48.05901</td>\n",
       "      <td>-122.3873</td>\n",
       "      <td>2016-12-03</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.977361</td>\n",
       "      <td>-2.263196</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-1.995497</td>\n",
       "      <td>-1.981796</td>\n",
       "      <td>-2.683351</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.107101</td>\n",
       "      <td>-1.338045</td>\n",
       "      <td>-0.379005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>483</th>\n",
       "      <td>121916KSBP01V1333</td>\n",
       "      <td>KSBP01V</td>\n",
       "      <td>Point Jefferson</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.74396</td>\n",
       "      <td>-122.4282</td>\n",
       "      <td>2016-12-19</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.992101</td>\n",
       "      <td>-2.178450</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-1.234803</td>\n",
       "      <td>-1.659473</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>0.154170</td>\n",
       "      <td>-1.500627</td>\n",
       "      <td>-0.530506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>484</th>\n",
       "      <td>122116LSNT01V1057</td>\n",
       "      <td>LSNT01V</td>\n",
       "      <td>Point Williams</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>N Central Basin</td>\n",
       "      <td>47.53333</td>\n",
       "      <td>-122.4333</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.154389</td>\n",
       "      <td>-2.034319</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-1.692999</td>\n",
       "      <td>-1.596273</td>\n",
       "      <td>-2.565419</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.285882</td>\n",
       "      <td>-1.574982</td>\n",
       "      <td>-0.640508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>485</th>\n",
       "      <td>122116NSEX01V1237</td>\n",
       "      <td>NSEX01V</td>\n",
       "      <td>East Passage</td>\n",
       "      <td>Central Basin</td>\n",
       "      <td>S Central Basin</td>\n",
       "      <td>47.35862</td>\n",
       "      <td>-122.3871</td>\n",
       "      <td>2016-12-21</td>\n",
       "      <td>2016</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.618915</td>\n",
       "      <td>-1.778781</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-2.169966</td>\n",
       "      <td>-1.734852</td>\n",
       "      <td>-2.787728</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.179354</td>\n",
       "      <td>-1.566102</td>\n",
       "      <td>-0.638187</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>486 rows × 96 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Key  Station                Site Name            Basin  \\\n",
       "0      032514DANAV1035    DANAV             Dana Passage      South Sound   \n",
       "1      040114sketv1001    SKETV  South Ketron/Solo Point      South Sound   \n",
       "2       040414ADIV1300     ADIV          Admiralty Inlet  Admiralty Inlet   \n",
       "3     040914ksbp010925  KSBP01V          Point Jefferson    Central Basin   \n",
       "4    040914lsnt01v1055  LSNT01V           Point Williams    Central Basin   \n",
       "..                 ...      ...                      ...              ...   \n",
       "481  112216NSEX01V1304  NSEX01V             East Passage    Central Basin   \n",
       "482     120316CAMV1200     CAMV              Camano Head    Whidbey Basin   \n",
       "483  121916KSBP01V1333  KSBP01V          Point Jefferson    Central Basin   \n",
       "484  122116LSNT01V1057  LSNT01V           Point Williams    Central Basin   \n",
       "485  122116NSEX01V1237  NSEX01V             East Passage    Central Basin   \n",
       "\n",
       "           Sub Basin       Lat       Lon Sample Date  Sample Year  \\\n",
       "0        South Sound  47.18327 -122.8307  2014-03-25         2014   \n",
       "1        South Sound  47.15243 -122.6586  2014-04-01         2014   \n",
       "2    Admiralty Inlet  48.00273 -122.6360  2014-04-04         2014   \n",
       "3    N Central Basin  47.74396 -122.4282  2014-04-09         2014   \n",
       "4    N Central Basin  47.53333 -122.4333  2014-04-09         2014   \n",
       "..               ...       ...       ...         ...          ...   \n",
       "481  S Central Basin  47.35862 -122.3871  2016-11-22         2016   \n",
       "482  S Whidbey Basin  48.05901 -122.3873  2016-12-03         2016   \n",
       "483  N Central Basin  47.74396 -122.4282  2016-12-19         2016   \n",
       "484  N Central Basin  47.53333 -122.4333  2016-12-21         2016   \n",
       "485  S Central Basin  47.35862 -122.3871  2016-12-21         2016   \n",
       "\n",
       "     Sample Month  ... L10Gastropods  L10Larvaceans  L10EuphausiidsJuv  \\\n",
       "0               3  ...     -1.963590      -1.759306          -3.000000   \n",
       "1               4  ...     -1.390759      -1.454509          -3.000000   \n",
       "2               4  ...     -0.768568      -1.338911          -3.000000   \n",
       "3               4  ...     -0.867468      -0.846542          -2.548761   \n",
       "4               4  ...     -1.798123      -0.933799          -3.000000   \n",
       "..            ...  ...           ...            ...                ...   \n",
       "481            11  ...     -0.451538      -1.187045          -2.722048   \n",
       "482            12  ...     -0.977361      -2.263196          -3.000000   \n",
       "483            12  ...     -0.992101      -2.178450          -3.000000   \n",
       "484            12  ...     -1.154389      -2.034319          -3.000000   \n",
       "485            12  ...     -0.618915      -1.778781          -3.000000   \n",
       "\n",
       "     L10HyperiidAmph  L10NonCalanoids  L10Jellies L10Tunicates  L10Total  \\\n",
       "0          -3.000000        -1.813082   -1.927517    -3.000000 -0.938520   \n",
       "1          -2.419121        -1.236035   -1.954179    -3.000000 -0.474971   \n",
       "2          -2.288450        -2.167170   -3.000000    -3.000000  0.143507   \n",
       "3          -1.611418        -1.625231   -3.000000    -2.248787 -0.101888   \n",
       "4          -2.920209        -1.637045   -2.677876    -3.000000 -0.336873   \n",
       "..               ...              ...         ...          ...       ...   \n",
       "481        -1.354277        -0.996189   -2.496160    -3.000000 -0.035765   \n",
       "482        -1.995497        -1.981796   -2.683351    -3.000000 -0.107101   \n",
       "483        -1.234803        -1.659473   -3.000000    -3.000000  0.154170   \n",
       "484        -1.692999        -1.596273   -2.565419    -3.000000 -0.285882   \n",
       "485        -2.169966        -1.734852   -2.787728    -3.000000 -0.179354   \n",
       "\n",
       "     L10mod_microzooplankton  L10mod_mesozooplankton  \n",
       "0                  -0.636064               -0.203705  \n",
       "1                  -0.553034               -0.345361  \n",
       "2                  -0.334718               -0.191273  \n",
       "3                  -0.484170               -0.286597  \n",
       "4                  -0.793377               -0.527014  \n",
       "..                       ...                     ...  \n",
       "481                -1.384651               -0.436282  \n",
       "482                -1.338045               -0.379005  \n",
       "483                -1.500627               -0.530506  \n",
       "484                -1.574982               -0.640508  \n",
       "485                -1.566102               -0.638187  \n",
       "\n",
       "[486 rows x 96 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "##Mean number of Calanoids grouped by sample month\n",
    "monthCala=data.groupby(['Sample Month', 'Calanoids'], as_index=False).mean()\n",
    "monthEuph=data.groupby(['Sample Month', 'Euphausiids'], as_index=False).mean()\n",
    "monthAmph=data.groupby(['Sample Month', 'Amphipods'], as_index=False).mean()\n",
    "monthCrab=data.groupby(['Sample Month', 'Crabs'], as_index=False).mean()\n",
    "monthNonCala=data.groupby(['Sample Month', 'NonCalanoids'], as_index=False).mean()\n",
    "monthLarv=data.groupby(['Sample Month', 'Larvaceans'], as_index=False).mean()\n",
    "monthGast=data.groupby(['Sample Month', 'Gastropods'], as_index=False).mean()\n",
    "monthJellies=data.groupby(['Sample Month', 'Jellies'], as_index=False).mean()\n",
    "monthModMicro=data.groupby(['Sample Month', 'mod_microzooplankton'], as_index=False).mean()\n",
    "monthModMeso=data.groupby(['Sample Month', 'mod_mesozooplankton'], as_index=False).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "testmean=data.groupby(['Sample Month']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [],
   "source": [
    "testsem=data.groupby(['Sample Month']).sem()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Lat</th>\n",
       "      <th>Lon</th>\n",
       "      <th>Sample Year</th>\n",
       "      <th>Mesh Size</th>\n",
       "      <th>Diameter (cm)</th>\n",
       "      <th>Z</th>\n",
       "      <th>Z_lower</th>\n",
       "      <th>Z_upper</th>\n",
       "      <th>Amphipoda-Hyperiidea</th>\n",
       "      <th>Amphipoda-Cyphocarididae</th>\n",
       "      <th>...</th>\n",
       "      <th>L10Gastropods</th>\n",
       "      <th>L10Larvaceans</th>\n",
       "      <th>L10EuphausiidsJuv</th>\n",
       "      <th>L10HyperiidAmph</th>\n",
       "      <th>L10NonCalanoids</th>\n",
       "      <th>L10Jellies</th>\n",
       "      <th>L10Tunicates</th>\n",
       "      <th>L10Total</th>\n",
       "      <th>L10mod_microzooplankton</th>\n",
       "      <th>L10mod_mesozooplankton</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Sample Month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>47.662811</td>\n",
       "      <td>-122.400838</td>\n",
       "      <td>2015.375000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>214.000000</td>\n",
       "      <td>187.500000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.201491</td>\n",
       "      <td>1.030582</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.068236</td>\n",
       "      <td>-2.276314</td>\n",
       "      <td>-2.990741</td>\n",
       "      <td>-1.680304</td>\n",
       "      <td>-1.788524</td>\n",
       "      <td>-2.787337</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.071158</td>\n",
       "      <td>-1.562488</td>\n",
       "      <td>-0.616619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>47.545303</td>\n",
       "      <td>-122.416200</td>\n",
       "      <td>2015.500000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>221.666667</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.395103</td>\n",
       "      <td>1.239294</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.205059</td>\n",
       "      <td>-2.197000</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-1.550350</td>\n",
       "      <td>-1.966319</td>\n",
       "      <td>-2.968229</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.176019</td>\n",
       "      <td>-1.498549</td>\n",
       "      <td>-0.645369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>47.741491</td>\n",
       "      <td>-122.534016</td>\n",
       "      <td>2015.516129</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>163.383871</td>\n",
       "      <td>148.032258</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.116852</td>\n",
       "      <td>0.456340</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.238079</td>\n",
       "      <td>-1.605854</td>\n",
       "      <td>-2.363406</td>\n",
       "      <td>-2.132281</td>\n",
       "      <td>-1.677756</td>\n",
       "      <td>-2.708622</td>\n",
       "      <td>-2.918808</td>\n",
       "      <td>-0.190426</td>\n",
       "      <td>-0.808475</td>\n",
       "      <td>-0.431088</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>47.827474</td>\n",
       "      <td>-122.561528</td>\n",
       "      <td>2015.063830</td>\n",
       "      <td>200.0</td>\n",
       "      <td>59.361702</td>\n",
       "      <td>151.223830</td>\n",
       "      <td>133.787234</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.312885</td>\n",
       "      <td>0.368899</td>\n",
       "      <td>...</td>\n",
       "      <td>-1.165122</td>\n",
       "      <td>-1.188293</td>\n",
       "      <td>-1.898653</td>\n",
       "      <td>-2.192522</td>\n",
       "      <td>-1.402973</td>\n",
       "      <td>-2.537302</td>\n",
       "      <td>-2.984017</td>\n",
       "      <td>0.049813</td>\n",
       "      <td>-0.543906</td>\n",
       "      <td>-0.249344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>47.902535</td>\n",
       "      <td>-122.601980</td>\n",
       "      <td>2015.046875</td>\n",
       "      <td>200.0</td>\n",
       "      <td>59.531250</td>\n",
       "      <td>140.292906</td>\n",
       "      <td>125.093750</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.446055</td>\n",
       "      <td>0.787286</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.897375</td>\n",
       "      <td>-1.349259</td>\n",
       "      <td>-1.578043</td>\n",
       "      <td>-1.836711</td>\n",
       "      <td>-1.031549</td>\n",
       "      <td>-2.225227</td>\n",
       "      <td>-2.987658</td>\n",
       "      <td>0.293324</td>\n",
       "      <td>-0.571678</td>\n",
       "      <td>-0.118078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>47.924064</td>\n",
       "      <td>-122.627632</td>\n",
       "      <td>2015.030769</td>\n",
       "      <td>200.0</td>\n",
       "      <td>59.538462</td>\n",
       "      <td>134.634769</td>\n",
       "      <td>121.630769</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.729695</td>\n",
       "      <td>0.940414</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.851987</td>\n",
       "      <td>-1.182542</td>\n",
       "      <td>-2.171991</td>\n",
       "      <td>-1.576642</td>\n",
       "      <td>-0.862115</td>\n",
       "      <td>-2.070806</td>\n",
       "      <td>-2.916647</td>\n",
       "      <td>0.197823</td>\n",
       "      <td>-0.504776</td>\n",
       "      <td>-0.142304</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>47.877797</td>\n",
       "      <td>-122.619903</td>\n",
       "      <td>2015.045455</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>134.863788</td>\n",
       "      <td>124.393939</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.961754</td>\n",
       "      <td>1.283190</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.572321</td>\n",
       "      <td>-1.189754</td>\n",
       "      <td>-2.202326</td>\n",
       "      <td>-1.585115</td>\n",
       "      <td>-0.820936</td>\n",
       "      <td>-1.986453</td>\n",
       "      <td>-2.978555</td>\n",
       "      <td>0.340145</td>\n",
       "      <td>-0.526707</td>\n",
       "      <td>-0.191426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>47.909050</td>\n",
       "      <td>-122.602115</td>\n",
       "      <td>2015.102941</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>137.324412</td>\n",
       "      <td>125.235294</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.871581</td>\n",
       "      <td>1.786725</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.558955</td>\n",
       "      <td>-1.327083</td>\n",
       "      <td>-2.104994</td>\n",
       "      <td>-1.594663</td>\n",
       "      <td>-0.746934</td>\n",
       "      <td>-2.147874</td>\n",
       "      <td>-2.946361</td>\n",
       "      <td>0.294895</td>\n",
       "      <td>-0.571960</td>\n",
       "      <td>-0.210450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>47.874174</td>\n",
       "      <td>-122.608813</td>\n",
       "      <td>2015.158730</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>135.982603</td>\n",
       "      <td>125.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.638771</td>\n",
       "      <td>1.739551</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.635785</td>\n",
       "      <td>-1.426287</td>\n",
       "      <td>-2.310343</td>\n",
       "      <td>-1.612528</td>\n",
       "      <td>-0.834343</td>\n",
       "      <td>-2.061648</td>\n",
       "      <td>-2.916899</td>\n",
       "      <td>0.223613</td>\n",
       "      <td>-0.736635</td>\n",
       "      <td>-0.138506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>47.688143</td>\n",
       "      <td>-122.535331</td>\n",
       "      <td>2015.125000</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>175.281250</td>\n",
       "      <td>153.750000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.564012</td>\n",
       "      <td>0.729872</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.718354</td>\n",
       "      <td>-1.740168</td>\n",
       "      <td>-2.241244</td>\n",
       "      <td>-1.484790</td>\n",
       "      <td>-0.967166</td>\n",
       "      <td>-2.207761</td>\n",
       "      <td>-2.890430</td>\n",
       "      <td>0.040892</td>\n",
       "      <td>-0.960298</td>\n",
       "      <td>-0.131159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>47.525856</td>\n",
       "      <td>-122.438278</td>\n",
       "      <td>2015.055556</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>213.574444</td>\n",
       "      <td>180.555556</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.304593</td>\n",
       "      <td>1.492369</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.739128</td>\n",
       "      <td>-1.848242</td>\n",
       "      <td>-2.753627</td>\n",
       "      <td>-1.583637</td>\n",
       "      <td>-1.188367</td>\n",
       "      <td>-2.436426</td>\n",
       "      <td>-2.969314</td>\n",
       "      <td>-0.023799</td>\n",
       "      <td>-1.240896</td>\n",
       "      <td>-0.345135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>47.666451</td>\n",
       "      <td>-122.403550</td>\n",
       "      <td>2014.916667</td>\n",
       "      <td>200.0</td>\n",
       "      <td>60.000000</td>\n",
       "      <td>213.750000</td>\n",
       "      <td>187.583333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.313695</td>\n",
       "      <td>1.556888</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.890417</td>\n",
       "      <td>-2.023904</td>\n",
       "      <td>-2.995699</td>\n",
       "      <td>-1.617466</td>\n",
       "      <td>-1.602192</td>\n",
       "      <td>-2.526959</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>-0.012034</td>\n",
       "      <td>-1.451460</td>\n",
       "      <td>-0.520892</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>12 rows × 87 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Lat         Lon  Sample Year  Mesh Size  Diameter (cm)  \\\n",
       "Sample Month                                                                 \n",
       "1             47.662811 -122.400838  2015.375000      200.0      60.000000   \n",
       "2             47.545303 -122.416200  2015.500000      200.0      60.000000   \n",
       "3             47.741491 -122.534016  2015.516129      200.0      60.000000   \n",
       "4             47.827474 -122.561528  2015.063830      200.0      59.361702   \n",
       "5             47.902535 -122.601980  2015.046875      200.0      59.531250   \n",
       "6             47.924064 -122.627632  2015.030769      200.0      59.538462   \n",
       "7             47.877797 -122.619903  2015.045455      200.0      60.000000   \n",
       "8             47.909050 -122.602115  2015.102941      200.0      60.000000   \n",
       "9             47.874174 -122.608813  2015.158730      200.0      60.000000   \n",
       "10            47.688143 -122.535331  2015.125000      200.0      60.000000   \n",
       "11            47.525856 -122.438278  2015.055556      200.0      60.000000   \n",
       "12            47.666451 -122.403550  2014.916667      200.0      60.000000   \n",
       "\n",
       "                       Z     Z_lower  Z_upper  Amphipoda-Hyperiidea  \\\n",
       "Sample Month                                                          \n",
       "1             214.000000  187.500000      0.0              0.201491   \n",
       "2             221.666667  190.000000      0.0              0.395103   \n",
       "3             163.383871  148.032258      0.0              0.116852   \n",
       "4             151.223830  133.787234      0.0              0.312885   \n",
       "5             140.292906  125.093750      0.0              0.446055   \n",
       "6             134.634769  121.630769      0.0              0.729695   \n",
       "7             134.863788  124.393939      0.0              0.961754   \n",
       "8             137.324412  125.235294      0.0              0.871581   \n",
       "9             135.982603  125.333333      0.0              0.638771   \n",
       "10            175.281250  153.750000      0.0              0.564012   \n",
       "11            213.574444  180.555556      0.0              0.304593   \n",
       "12            213.750000  187.583333      0.0              0.313695   \n",
       "\n",
       "              Amphipoda-Cyphocarididae  ...  L10Gastropods  L10Larvaceans  \\\n",
       "Sample Month                            ...                                 \n",
       "1                             1.030582  ...      -1.068236      -2.276314   \n",
       "2                             1.239294  ...      -1.205059      -2.197000   \n",
       "3                             0.456340  ...      -1.238079      -1.605854   \n",
       "4                             0.368899  ...      -1.165122      -1.188293   \n",
       "5                             0.787286  ...      -0.897375      -1.349259   \n",
       "6                             0.940414  ...      -0.851987      -1.182542   \n",
       "7                             1.283190  ...      -0.572321      -1.189754   \n",
       "8                             1.786725  ...      -0.558955      -1.327083   \n",
       "9                             1.739551  ...      -0.635785      -1.426287   \n",
       "10                            0.729872  ...      -0.718354      -1.740168   \n",
       "11                            1.492369  ...      -0.739128      -1.848242   \n",
       "12                            1.556888  ...      -0.890417      -2.023904   \n",
       "\n",
       "              L10EuphausiidsJuv  L10HyperiidAmph  L10NonCalanoids  L10Jellies  \\\n",
       "Sample Month                                                                    \n",
       "1                     -2.990741        -1.680304        -1.788524   -2.787337   \n",
       "2                     -3.000000        -1.550350        -1.966319   -2.968229   \n",
       "3                     -2.363406        -2.132281        -1.677756   -2.708622   \n",
       "4                     -1.898653        -2.192522        -1.402973   -2.537302   \n",
       "5                     -1.578043        -1.836711        -1.031549   -2.225227   \n",
       "6                     -2.171991        -1.576642        -0.862115   -2.070806   \n",
       "7                     -2.202326        -1.585115        -0.820936   -1.986453   \n",
       "8                     -2.104994        -1.594663        -0.746934   -2.147874   \n",
       "9                     -2.310343        -1.612528        -0.834343   -2.061648   \n",
       "10                    -2.241244        -1.484790        -0.967166   -2.207761   \n",
       "11                    -2.753627        -1.583637        -1.188367   -2.436426   \n",
       "12                    -2.995699        -1.617466        -1.602192   -2.526959   \n",
       "\n",
       "              L10Tunicates  L10Total  L10mod_microzooplankton  \\\n",
       "Sample Month                                                    \n",
       "1                -3.000000 -0.071158                -1.562488   \n",
       "2                -3.000000 -0.176019                -1.498549   \n",
       "3                -2.918808 -0.190426                -0.808475   \n",
       "4                -2.984017  0.049813                -0.543906   \n",
       "5                -2.987658  0.293324                -0.571678   \n",
       "6                -2.916647  0.197823                -0.504776   \n",
       "7                -2.978555  0.340145                -0.526707   \n",
       "8                -2.946361  0.294895                -0.571960   \n",
       "9                -2.916899  0.223613                -0.736635   \n",
       "10               -2.890430  0.040892                -0.960298   \n",
       "11               -2.969314 -0.023799                -1.240896   \n",
       "12               -3.000000 -0.012034                -1.451460   \n",
       "\n",
       "              L10mod_mesozooplankton  \n",
       "Sample Month                          \n",
       "1                          -0.616619  \n",
       "2                          -0.645369  \n",
       "3                          -0.431088  \n",
       "4                          -0.249344  \n",
       "5                          -0.118078  \n",
       "6                          -0.142304  \n",
       "7                          -0.191426  \n",
       "8                          -0.210450  \n",
       "9                          -0.138506  \n",
       "10                         -0.131159  \n",
       "11                         -0.345135  \n",
       "12                         -0.520892  \n",
       "\n",
       "[12 rows x 87 columns]"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "testmean"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "meanmonthCala=data.groupby(['Calanoids'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthEuph=data.groupby(['Euphausiids'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthAmph=data.groupby(['Amphipods'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthCrab=data.groupby(['Crabs'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthNonCala=data.groupby(['NonCalanoids'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLarv=data.groupby(['Larvaceans'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthGast=data.groupby(['Gastropods'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthJellies=data.groupby(['Jellies'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthTotal=data.groupby(['Total'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "\n",
    "meanmonthModMicro=data.groupby(['mod_microzooplankton'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthModMeso=data.groupby(['mod_mesozooplankton'], as_index=False).mean().groupby(['Sample Month']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "meanmonthLogCala=data.groupby(['L10Calanoids'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogEuph=data.groupby(['L10Euphausiids'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogAmph=data.groupby(['L10Amphipods'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogCrab=data.groupby(['L10Crabs'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogNonCala=data.groupby(['L10NonCalanoids'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogLarv=data.groupby(['L10Larvaceans'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogGast=data.groupby(['L10Gastropods'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogJellies=data.groupby(['L10Jellies'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogTotal=data.groupby(['L10Total'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "\n",
    "meanmonthLogModMicro=data.groupby(['L10mod_microzooplankton'], as_index=False).mean().groupby(['Sample Month']).mean()\n",
    "meanmonthLogModMeso=data.groupby(['L10mod_mesozooplankton'], as_index=False).mean().groupby(['Sample Month']).mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "geomeanCala=gmean(meanmonthCala.loc[:,'Calanoids'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7449109049870318"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geomeanCala"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "##sample R code for geometric mean conversion of log values\n",
    "#geoMean <- function(x, ...){\n",
    "#    xlog <- log(x)\n",
    "#    exp(mean(xlog[is.finite(xlog)]))\n",
    "#}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.5)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,4,figsize=(20,5))\n",
    "fig.suptitle('Puget Sound', fontsize=24)\n",
    "fig.subplots_adjust(top=0.8)\n",
    "ax[0].plot(10**(meanmonthLogCala['L10Calanoids']),'r-')\n",
    "ax[0].plot(10**(test['L10Calanoids']-.001),'b--')\n",
    "ax[1].plot(10**(meanmonthLogEuph['L10Euphausiids']),'r-')\n",
    "ax[1].plot(10**(test['L10Euphausiids']-.001),'b--')\n",
    "ax[2].plot(10**(meanmonthLogAmph['L10Amphipods']),'r--')\n",
    "ax[3].plot(10**(meanmonthLogCrab['L10Crabs']),'r--')\n",
    "ax[0].set_title('Calanoid Seasonal Cycle')\n",
    "ax[1].set_title('Euphausiid Seasonal Cycle')\n",
    "ax[2].set_title('Amphipod Seasonal Cycle')\n",
    "ax[3].set_title('Decapod Seasonal Cycle')\n",
    "ax[0].set_ylabel('Mean Biomass ($\\mu$M N)')\n",
    "ax[0].set_xlim(0,12)\n",
    "ax[1].set_xlim(0,12)\n",
    "ax[2].set_xlim(0,12)\n",
    "ax[3].set_xlim(0,12)\n",
    "ax[0].set_ylim(0,1.5)\n",
    "ax[1].set_ylim(0,1.5)\n",
    "ax[2].set_ylim(0,1.5)\n",
    "ax[3].set_ylim(0,1.5)\n",
    "\n",
    "fig,ax=plt.subplots(1,4,figsize=(20,5))\n",
    "ax[0].plot(10**(meanmonthLogNonCala['L10NonCalanoids']),'r--')\n",
    "ax[1].plot(10**(meanmonthLogLarv['L10Larvaceans']),'r--')\n",
    "ax[2].plot(10**(meanmonthGast['L10Gastropods']),'r--')\n",
    "ax[3].plot(10**(meanmonthLogJellies['L10Jellies']),'r--')\n",
    "ax[0].set_title('Non Calanoid Seasonal Cycle')\n",
    "ax[1].set_title('Larvacean Seasonal Cycle')\n",
    "ax[2].set_title('Gastropod Seasonal Cycle')\n",
    "ax[3].set_title('Jellies Seasonal Cycle')\n",
    "ax[0].set_ylabel('Mean Biomass ($\\mu$M N)')\n",
    "ax[0].set_xlim(0,12)\n",
    "ax[1].set_xlim(0,12)\n",
    "ax[2].set_xlim(0,12)\n",
    "ax[3].set_xlim(0,12)\n",
    "ax[0].set_ylim(0,1.5)\n",
    "ax[1].set_ylim(0,1.5)\n",
    "ax[2].set_ylim(0,1.5)\n",
    "ax[3].set_ylim(0,1.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2, 12)"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape([testmean['L10Calanoids']-testsem['L10Calanoids'],\n",
    " testmean['L10Calanoids']+testsem['L10Calanoids']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.0, 1.5)"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x360 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,ax=plt.subplots(1,4,figsize=(20,5))\n",
    "fig.suptitle('Puget Sound', fontsize=24)\n",
    "fig.subplots_adjust(top=0.8)\n",
    "ax[0].errorbar(test.index,logt_inv(testmean['L10Calanoids']),\n",
    "               yerr=logt_inv(np.array([testmean['L10Calanoids']-testsem['L10Calanoids'],\n",
    "                 testmean['L10Calanoids']+testsem['L10Calanoids']])),\n",
    "               fmt='ro',capsize=5)\n",
    "ax[0].plot(10**(test['L10Calanoids']-.001),'b--')\n",
    "ax[1].plot(10**(meanmonthLogEuph['L10Euphausiids']),'r-')\n",
    "ax[1].plot(10**(test['L10Euphausiids']-.001),'b--')\n",
    "ax[2].plot(10**(meanmonthLogAmph['L10Amphipods']),'r--')\n",
    "ax[3].plot(10**(meanmonthLogCrab['L10Crabs']),'r--')\n",
    "ax[0].set_title('Calanoid Seasonal Cycle')\n",
    "ax[1].set_title('Euphausiid Seasonal Cycle')\n",
    "ax[2].set_title('Amphipod Seasonal Cycle')\n",
    "ax[3].set_title('Decapod Seasonal Cycle')\n",
    "ax[0].set_ylabel('Mean Biomass ($\\mu$M N)')\n",
    "ax[0].set_xlim(0,12)\n",
    "ax[1].set_xlim(0,12)\n",
    "ax[2].set_xlim(0,12)\n",
    "ax[3].set_xlim(0,12)\n",
    "ax[0].set_ylim(0,2.3)\n",
    "ax[1].set_ylim(0,1.5)\n",
    "ax[2].set_ylim(0,1.5)\n",
    "ax[3].set_ylim(0,1.5)\n",
    "\n",
    "fig,ax=plt.subplots(1,4,figsize=(20,5))\n",
    "ax[0].plot(10**(meanmonthLogNonCala['L10NonCalanoids']),'r--')\n",
    "ax[1].plot(10**(meanmonthLogLarv['L10Larvaceans']),'r--')\n",
    "ax[2].plot(10**(meanmonthGast['L10Gastropods']),'r--')\n",
    "ax[3].plot(10**(meanmonthLogJellies['L10Jellies']),'r--')\n",
    "ax[0].set_title('Non Calanoid Seasonal Cycle')\n",
    "ax[1].set_title('Larvacean Seasonal Cycle')\n",
    "ax[2].set_title('Gastropod Seasonal Cycle')\n",
    "ax[3].set_title('Jellies Seasonal Cycle')\n",
    "ax[0].set_ylabel('Mean Biomass ($\\mu$M N)')\n",
    "ax[0].set_xlim(0,12)\n",
    "ax[1].set_xlim(0,12)\n",
    "ax[2].set_xlim(0,12)\n",
    "ax[3].set_xlim(0,12)\n",
    "ax[0].set_ylim(0,1.5)\n",
    "ax[1].set_ylim(0,1.5)\n",
    "ax[2].set_ylim(0,1.5)\n",
    "ax[3].set_ylim(0,1.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "monthTotal=data.groupby(['Sample Month', 'Total'], as_index=False).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(12,2.5))\n",
    "ax.plot(10**(meanmonthLogTotal['L10Total']),'--',color='blue',label='Obs Total Zoop')\n",
    "ax.set_ylim(0,3)\n",
    "ax.set_title('Puget Sound Observation Zooplankton Seasonal Cycle')\n",
    "ax.set_ylabel('Concentration ($\\mu$M N)',fontsize=10)\n",
    "\n",
    "fig,ax=plt.subplots(1,1,figsize=(12,2.5))\n",
    "ax.plot(10**(meanmonthLogModMeso['L10mod_mesozooplankton']),'--',color='red',label='Model Microzoop')\n",
    "ax.set_ylim(0,3)\n",
    "ax.set_title('Model Mesozooplankton Seasonal Cycle')\n",
    "ax.set_ylabel('Concentration ($\\mu$M N)',fontsize=10)\n",
    "\n",
    "fig,ax=plt.subplots(1,1,figsize=(12,2.5))\n",
    "ax.plot(10**(meanmonthLogModMicro['L10mod_microzooplankton']),'--',color='darkorange',label='Model Microzoop')\n",
    "ax.set_ylim(0,3)\n",
    "ax.set_title('Model Microzooplankton Seasonal Cycle')\n",
    "ax.set_ylabel('Concentration ($\\mu$M N)',fontsize=10)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "cm1=cmocean.cm.thermal\n",
    "with nc.Dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/bathymetry_201702.nc') as bathy:\n",
    "    bathylon=np.copy(bathy.variables['nav_lon'][:,:])\n",
    "    bathylat=np.copy(bathy.variables['nav_lat'][:,:])\n",
    "    bathyZ=np.copy(bathy.variables['Bathymetry'][:,:])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (6,6))\n",
    "with nc.Dataset('/ocean/ksuchy/MOAD/NEMO-forcing/grid/bathymetry_201702.nc') as grid:\n",
    "    viz_tools.plot_coastline(ax, grid, coords = 'map',isobath=.1)\n",
    "colors=('teal','green','firebrick','darkorange','darkviolet','fuchsia',\n",
    "        'royalblue','darkgoldenrod','mediumspringgreen','deepskyblue')\n",
    "datreg=dict()\n",
    "for ind, iregion in enumerate(data.Basin.unique()):\n",
    "    datreg[iregion] = data.loc[data.Basin==iregion]\n",
    "    ax.plot(datreg[iregion]['Lon'], datreg[iregion]['Lat'],'.',\n",
    "            color = colors[ind], label=iregion)\n",
    "ax.set_ylim(47,51)\n",
    "ax.legend(bbox_to_anchor=[1,.6,0,0])\n",
    "ax.set_xlim(-126, -120);\n",
    "ax.set_title('Observation Locations');\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def byRegion(ax,obsvar,modvar,lims):\n",
    "    PS=[]\n",
    "    for ind, iregion in enumerate(data.Basin.unique()):\n",
    "        #ax.plot(datreg[iregion]['Lon'], datreg[iregion]['Lat'],'.',\n",
    "                #color = colors[ind], label=iregion)\n",
    "        PS0=et.varvarPlot(ax,datreg[iregion],obsvar,modvar,\n",
    "                          cols=(colors[ind],),lname=iregion)\n",
    "        PS.append(PS0)\n",
    "    l=ax.legend(handles=[ip[0][0] for ip in PS])\n",
    "    ax.set_xlabel('Obs')\n",
    "    ax.set_ylabel('Model')\n",
    "    ax.plot(lims,lims,'k-',alpha=.5)\n",
    "    ax.set_xlim(lims)\n",
    "    ax.set_ylim(lims)\n",
    "    ax.set_aspect(1)\n",
    "    return PS,l"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "data['Month']=[ii.month for ii in data['dtUTC']]\n",
    "JF=data.loc[(data.Month==1)|(data.Month==2)]\n",
    "MAM=data.loc[(data.Month==3)|(data.Month==4)|(data.Month==5)]\n",
    "JJA=data.loc[(data.Month==6)|(data.Month==7)|(data.Month==8)]\n",
    "SOND=data.loc[(data.Month==9)|(data.Month==10)|(data.Month==11)|(data.Month==12)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def bySeason(ax,obsvar,modvar,lims):\n",
    "    for axi in ax:\n",
    "        axi.plot(lims,lims,'k-')\n",
    "        axi.set_xlim(lims)\n",
    "        axi.set_ylim(lims)\n",
    "        axi.set_aspect(1)\n",
    "        axi.set_xlabel('Obs')\n",
    "        axi.set_ylabel('Model')\n",
    "    PS=et.varvarPlot(ax[0],JF,obsvar,modvar,cols=('crimson','darkturquoise','navy'))\n",
    "    ax[0].set_title('Winter')\n",
    "    PS=et.varvarPlot(ax[1],MAM,obsvar,modvar,cols=('crimson','darkturquoise','navy'))\n",
    "    ax[1].set_title('Spring')\n",
    "    PS=et.varvarPlot(ax[2],JJA,obsvar,modvar,cols=('crimson','darkturquoise','navy'))\n",
    "    ax[2].set_title('Summer')\n",
    "    PS=et.varvarPlot(ax[3],SOND,obsvar,modvar,cols=('crimson','darkturquoise','navy'))\n",
    "    ax[3].set_title('Autumn')\n",
    "    return "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Calanoids','L10mod_mesozooplankton',(-2,2))\n",
    "ax.set_title('Log10 Calanoids ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Calanoids','L10mod_mesozooplankton',(-2,2))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10NonCalanoids','L10mod_mesozooplankton',(-2,2))\n",
    "ax.set_title('Log10 NonCalanoids ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10NonCalanoids','L10mod_mesozooplankton',(-2,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Euphausiids','L10mod_mesozooplankton',(-3,3))\n",
    "ax.set_title('Log10 Euphausiids ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Euphausiids','L10mod_mesozooplankton',(-3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10EuphausiidsJuv','L10mod_mesozooplankton',(-3,3))\n",
    "ax.set_title('Log10 Euphausiid Juveniles ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10EuphausiidsJuv','L10mod_mesozooplankton',(-3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Crabs','L10mod_mesozooplankton',(-3,2))\n",
    "ax.set_title('L10 Crabs($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Crabs','L10mod_mesozooplankton',(-3,2))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Amphipods','L10mod_mesozooplankton',(-3,2))\n",
    "ax.set_title('L10 Amphipods($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Amphipods','L10mod_mesozooplankton',(-3,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10HyperiidAmph','L10mod_mesozooplankton',(-3,2))\n",
    "ax.set_title('L10 Hyperiid Amphipods($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10HyperiidAmph','L10mod_mesozooplankton',(-3,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Larvaceans','L10mod_mesozooplankton',(-3,3))\n",
    "ax.set_title('Log10 Larvaceans ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Larvaceans','L10mod_mesozooplankton',(-3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Tunicates','L10mod_mesozooplankton',(-3,3))\n",
    "ax.set_title('Log10 Tunicates ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Tunicates','L10mod_mesozooplankton',(-3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(1,1,figsize = (16,7))     \n",
    "PS,l=byRegion(ax,'L10Jellies','L10mod_mesozooplankton',(-3,3))\n",
    "ax.set_title('Log10 Jellies ($\\mu$M) By Region')\n",
    "ax.legend(bbox_to_anchor=(1.1, 1.05))\n",
    "\n",
    "fig, ax = plt.subplots(1,4,figsize = (16,3.3))\n",
    "bySeason(ax,'L10Jellies','L10mod_mesozooplankton',(-3,3))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(2,4,figsize=(15,7))\n",
    "fig.subplots_adjust(wspace=.4)\n",
    "fig.subplots_adjust(hspace=.6)\n",
    "ax=ax.flatten()\n",
    "\n",
    "taxa=('Amphipods', 'Euphausiids','Calanoids','NonCalanoids', 'Crabs','Larvaceans','Gastropods','Jellies')\n",
    "\n",
    "mvar1=data['mod_microzooplankton']\n",
    "mvar2=data['mod_mesozooplankton']\n",
    "\n",
    "for ii in range(0,len(taxa)):\n",
    "    ax[ii].plot(logt(data.loc[:,[taxa[ii]]].values),logt(mvar1),'.',ms=1,color='blue',label='Microzoop')\n",
    "    ax[ii].plot(logt(data.loc[:,[taxa[ii]]].values),logt(mvar2),'.',ms=1,color='red',label='Mesozoop')\n",
    "    ax[ii].set_ylabel('Model Class')\n",
    "    ax[ii].set_xlabel(taxa[ii])\n",
    "    ax[ii].set_title('log10[$\\mu$M +.001]')\n",
    "    ax[ii].plot((-3,3),(-3,3),'k-',alpha=.2)\n",
    "    ax[ii].set_xlim((-3,1))\n",
    "    ax[ii].set_ylim((-3,1))\n",
    "    ax[ii].set_aspect(1)\n",
    "ax[0].legend(loc=2, fontsize = 'small')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def yd(idt):\n",
    "    if type(idt)==dt.datetime:\n",
    "        yd=(idt-dt.datetime(idt.year-1,12,31)).days\n",
    "    else: # assume array or pandas\n",
    "        yd=[(ii-dt.datetime(ii.year-1,12,31)).days for ii in idt]\n",
    "    return yd\n",
    "\n",
    "data['yd']=yd(data['dtUTC'])\n",
    "data['Year']=[ii.year for ii in data['dtUTC']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Calanoids']+data['Euphausiids']+data['Amphipods']+data['Crabs']+data['Larvaceans']+data['Gastropods'])+data['NonCalanoids']+data['Jellies'],logt(data['mod_mesozooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ All Groups vs Model Mesozooplankton+ 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-1.5,1.5)\n",
    "ax.set_ylim(-1.5,1.5);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Calanoids']+data['Euphausiids']+data['Amphipods']),logt(data['mod_mesozooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ Cala Euph Amph vs Model Mesozooplankton + 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-1.5,1.5)\n",
    "ax.set_ylim(-1.5,1.5);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Calanoids']+data['NonCalanoids']),logt(data['mod_mesozooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ Copepods Only vs Model Mesozooplankton + 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-1.5,1.5)\n",
    "ax.set_ylim(-1.5,1.5);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Calanoids']+data['Euphausiids']+data['Amphipods']+data['Crabs']+data['Larvaceans']+data['Gastropods'])+data['NonCalanoids']+data['Jellies'],logt(data['mod_microzooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ All Groups vs Mod Micro + 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-2,2)\n",
    "ax.set_ylim(-2,2);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Calanoids']+data['Euphausiids']+data['Amphipods']),logt(data['mod_microzooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ Cala Euph Amph vs Mod Micro + 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-2,2)\n",
    "ax.set_ylim(-2,2);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Calanoids']+data['NonCalanoids']),logt(data['mod_microzooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ Copepods vs Mod Micro + 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-2,2)\n",
    "ax.set_ylim(-2,2);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig,ax=plt.subplots(1,1,figsize=(7,7))\n",
    "m=ax.scatter(logt(data['Larvaceans']),logt(data['mod_microzooplankton']),\n",
    "          c=data['yd'],s=5,cmap=cmocean.cm.phase)\n",
    "\n",
    "ax.set_title('log10[ Larvaceans vs Mod Micro + 0.001] By Year Day')\n",
    "ax.set_xlabel('Obs')\n",
    "ax.set_ylabel('Model')\n",
    "ax.plot((-6,5),(-6,5),'r-',alpha=.3)\n",
    "ax.set_xlim(-3,3)\n",
    "ax.set_ylim(-3,3);\n",
    "fig.colorbar(m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Amph=data['Amphipoda']\n",
    "#data['L10Euphausiids']=logt(data['Euphausiids'])\n",
    "#data['L10Crabs']=logt(data['Crabs'])\n",
    "#data['L10Calanoids']=logt(data['Calanoids'])\n",
    "data['L10Gastropods']=logt(data['Gastropods'])\n",
    "data['L10Larvaceans']=logt(data['Larvaceans'])\n",
    "data['L10EuphausiidsJuv']=logt(data['EuphausiidsJuv'])\n",
    "data['L10HyperiidAmph']=logt(data['HyperiidAmph'])\n",
    "data['L10NonCalanoids']=logt(data['NonCalanoids'])\n",
    "data['L10Jellies']=logt(data['Jellies'])\n",
    "data['L10Tunicates']=logt(data['Tunicates'])\n",
    "data['L10mod_microzooplankton']=logt(data['mod_microzooplankton'])\n",
    "data['L10mod_mesozooplankton']=logt(data['mod_mesozooplankton'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "obsvar='Calanoids'\n",
    "modvar='mod_mesozooplankton'\n",
    "start_date=dt.datetime(2015,1,1)\n",
    "end_date=dt.datetime(2015,12,31)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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