{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Pandas is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language.\n",
    "\n",
    "Library documentation: <a>http://pandas.pydata.org/</a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### General"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     1\n",
       "1     3\n",
       "2     5\n",
       "3   NaN\n",
       "4     6\n",
       "5     8\n",
       "dtype: float64"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a series\n",
    "s = pd.Series([1,3,5,np.nan,6,8])\n",
    "s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.469292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td>-0.534227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.809526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.161051</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td> 0.474422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td> 0.000782</td>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.033628</td>\n",
       "      <td>-0.419772</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  0.205240  0.527603  0.610052  0.469292\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  0.862170\n",
       "2013-01-03 -1.462109  0.483201 -1.044973 -0.534227\n",
       "2013-01-04  0.719197 -0.499809  1.145788 -0.809526\n",
       "2013-01-05 -1.161051 -0.115774 -0.624413  0.474422\n",
       "2013-01-06  0.000782  0.146544  0.033628 -0.419772"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create a data frame\n",
    "dates = pd.date_range('20130101',periods=6)\n",
    "df = pd.DataFrame(np.random.randn(6,4),index=dates,columns=list('ABCD'))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td> 1</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td> 1</td>\n",
       "      <td> 3</td>\n",
       "      <td> foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> 1</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td> 1</td>\n",
       "      <td> 3</td>\n",
       "      <td> foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> 1</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td> 1</td>\n",
       "      <td> 3</td>\n",
       "      <td> foo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> 1</td>\n",
       "      <td>2013-01-02</td>\n",
       "      <td> 1</td>\n",
       "      <td> 3</td>\n",
       "      <td> foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A          B  C  D    E\n",
       "0  1 2013-01-02  1  3  foo\n",
       "1  1 2013-01-02  1  3  foo\n",
       "2  1 2013-01-02  1  3  foo\n",
       "3  1 2013-01-02  1  3  foo"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# another way to create a data frame\n",
    "df2 = pd.DataFrame(\n",
    "    { 'A' : 1.,\n",
    "      'B' : pd.Timestamp('20130102'),\n",
    "      'C' : pd.Series(1,index=list(range(4)),dtype='float32'),\n",
    "      'D' : np.array([3] * 4,dtype='int32'),\n",
    "      'E' : 'foo' })\n",
    "df2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A           float64\n",
       "B    datetime64[ns]\n",
       "C           float32\n",
       "D             int32\n",
       "E            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.469292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td>-0.534227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.809526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.161051</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td> 0.474422</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  0.205240  0.527603  0.610052  0.469292\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  0.862170\n",
       "2013-01-03 -1.462109  0.483201 -1.044973 -0.534227\n",
       "2013-01-04  0.719197 -0.499809  1.145788 -0.809526\n",
       "2013-01-05 -1.161051 -0.115774 -0.624413  0.474422"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<class 'pandas.tseries.index.DatetimeIndex'>\n",
       "[2013-01-01, ..., 2013-01-06]\n",
       "Length: 6, Freq: D, Timezone: None"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index([u'A', u'B', u'C', u'D'], dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  2.05240362e-01,   5.27602841e-01,   6.10052272e-01,\n",
       "          4.69292270e-01],\n",
       "       [  8.18112883e-01,  -8.94389618e-01,  -1.60283098e+00,\n",
       "          8.62169894e-01],\n",
       "       [ -1.46210940e+00,   4.83201108e-01,  -1.04497297e+00,\n",
       "         -5.34226832e-01],\n",
       "       [  7.19196807e-01,  -4.99809344e-01,   1.14578824e+00,\n",
       "         -8.09525609e-01],\n",
       "       [ -1.16105080e+00,  -1.15774007e-01,  -6.24412514e-01,\n",
       "          4.74421893e-01],\n",
       "       [  7.82298420e-04,   1.46543576e-01,   3.36282758e-02,\n",
       "         -4.19771560e-01]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td> 6.000000</td>\n",
       "      <td> 6.000000</td>\n",
       "      <td> 6.000000</td>\n",
       "      <td> 6.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>-0.146638</td>\n",
       "      <td>-0.058771</td>\n",
       "      <td>-0.247125</td>\n",
       "      <td> 0.007060</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td> 0.957650</td>\n",
       "      <td> 0.561381</td>\n",
       "      <td> 1.036400</td>\n",
       "      <td> 0.679012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td>-0.809526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>-0.870593</td>\n",
       "      <td>-0.403801</td>\n",
       "      <td>-0.939833</td>\n",
       "      <td>-0.505613</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td> 0.103011</td>\n",
       "      <td> 0.015385</td>\n",
       "      <td>-0.295392</td>\n",
       "      <td> 0.024760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td> 0.590708</td>\n",
       "      <td> 0.399037</td>\n",
       "      <td> 0.465946</td>\n",
       "      <td> 0.473139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              A         B         C         D\n",
       "count  6.000000  6.000000  6.000000  6.000000\n",
       "mean  -0.146638 -0.058771 -0.247125  0.007060\n",
       "std    0.957650  0.561381  1.036400  0.679012\n",
       "min   -1.462109 -0.894390 -1.602831 -0.809526\n",
       "25%   -0.870593 -0.403801 -0.939833 -0.505613\n",
       "50%    0.103011  0.015385 -0.295392  0.024760\n",
       "75%    0.590708  0.399037  0.465946  0.473139\n",
       "max    0.818113  0.527603  1.145788  0.862170"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# quick data summary\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>2013-01-01 00:00:00</th>\n",
       "      <th>2013-01-02 00:00:00</th>\n",
       "      <th>2013-01-03 00:00:00</th>\n",
       "      <th>2013-01-04 00:00:00</th>\n",
       "      <th>2013-01-05 00:00:00</th>\n",
       "      <th>2013-01-06 00:00:00</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-1.161051</td>\n",
       "      <td> 0.000782</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td> 0.527603</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td> 0.146544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td> 0.610052</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td> 0.033628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>D</th>\n",
       "      <td> 0.469292</td>\n",
       "      <td> 0.862170</td>\n",
       "      <td>-0.534227</td>\n",
       "      <td>-0.809526</td>\n",
       "      <td> 0.474422</td>\n",
       "      <td>-0.419772</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   2013-01-01  2013-01-02  2013-01-03  2013-01-04  2013-01-05  2013-01-06\n",
       "A    0.205240    0.818113   -1.462109    0.719197   -1.161051    0.000782\n",
       "B    0.527603   -0.894390    0.483201   -0.499809   -0.115774    0.146544\n",
       "C    0.610052   -1.602831   -1.044973    1.145788   -0.624413    0.033628\n",
       "D    0.469292    0.862170   -0.534227   -0.809526    0.474422   -0.419772"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>D</th>\n",
       "      <th>C</th>\n",
       "      <th>B</th>\n",
       "      <th>A</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.469292</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.205240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.862170</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td> 0.818113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.534227</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.462109</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.809526</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 0.719197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td> 0.474422</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-1.161051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>-0.419772</td>\n",
       "      <td> 0.033628</td>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.000782</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   D         C         B         A\n",
       "2013-01-01  0.469292  0.610052  0.527603  0.205240\n",
       "2013-01-02  0.862170 -1.602831 -0.894390  0.818113\n",
       "2013-01-03 -0.534227 -1.044973  0.483201 -1.462109\n",
       "2013-01-04 -0.809526  1.145788 -0.499809  0.719197\n",
       "2013-01-05  0.474422 -0.624413 -0.115774 -1.161051\n",
       "2013-01-06 -0.419772  0.033628  0.146544  0.000782"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# axis 0 is index, axis 1 is columns\n",
    "df.sort_index(axis=1, ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.809526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.161051</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td> 0.474422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td> 0.000782</td>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.033628</td>\n",
       "      <td>-0.419772</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td>-0.534227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.469292</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  0.862170\n",
       "2013-01-04  0.719197 -0.499809  1.145788 -0.809526\n",
       "2013-01-05 -1.161051 -0.115774 -0.624413  0.474422\n",
       "2013-01-06  0.000782  0.146544  0.033628 -0.419772\n",
       "2013-01-03 -1.462109  0.483201 -1.044973 -0.534227\n",
       "2013-01-01  0.205240  0.527603  0.610052  0.469292"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# can sort by values too\n",
    "df.sort(columns='B')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-01-01    0.205240\n",
       "2013-01-02    0.818113\n",
       "2013-01-03   -1.462109\n",
       "2013-01-04    0.719197\n",
       "2013-01-05   -1.161051\n",
       "2013-01-06    0.000782\n",
       "Freq: D, Name: A, dtype: float64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select a column (yields a series)\n",
    "df['A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-01-01    0.205240\n",
       "2013-01-02    0.818113\n",
       "2013-01-03   -1.462109\n",
       "2013-01-04    0.719197\n",
       "2013-01-05   -1.161051\n",
       "2013-01-06    0.000782\n",
       "Freq: D, Name: A, dtype: float64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# column names also attached to the object\n",
    "df.A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.469292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td>-0.534227</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  0.205240  0.527603  0.610052  0.469292\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  0.862170\n",
       "2013-01-03 -1.462109  0.483201 -1.044973 -0.534227"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# slicing works\n",
    "df[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td>-0.534227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.809526</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  0.862170\n",
       "2013-01-03 -1.462109  0.483201 -1.044973 -0.534227\n",
       "2013-01-04  0.719197 -0.499809  1.145788 -0.809526"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['20130102':'20130104']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0.205240\n",
       "B    0.527603\n",
       "C    0.610052\n",
       "D    0.469292\n",
       "Name: 2013-01-01 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# cross-section using a label\n",
    "df.loc[dates[0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.20524036189008577"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# getting a scalar value\n",
    "df.loc[dates[0], 'A']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    0.719197\n",
       "B   -0.499809\n",
       "C    1.145788\n",
       "D   -0.809526\n",
       "Name: 2013-01-04 00:00:00, dtype: float64"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# select via position\n",
    "df.iloc[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.161051</td>\n",
       "      <td>-0.115774</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B\n",
       "2013-01-04  0.719197 -0.499809\n",
       "2013-01-05 -1.161051 -0.115774"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[3:5,0:2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-0.624413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.033628</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   B         C\n",
       "2013-01-01  0.527603  0.610052\n",
       "2013-01-02 -0.894390 -1.602831\n",
       "2013-01-03  0.483201 -1.044973\n",
       "2013-01-04 -0.499809  1.145788\n",
       "2013-01-05 -0.115774 -0.624413\n",
       "2013-01-06  0.146544  0.033628"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# column slicing\n",
    "df.iloc[:,1:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.89438961765370562"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get a value by index\n",
    "df.iloc[1,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.469292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>-0.809526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td> 0.000782</td>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.033628</td>\n",
       "      <td>-0.419772</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  0.205240  0.527603  0.610052  0.469292\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  0.862170\n",
       "2013-01-04  0.719197 -0.499809  1.145788 -0.809526\n",
       "2013-01-06  0.000782  0.146544  0.033628 -0.419772"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# boolean indexing\n",
    "df[df.A > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.205240</td>\n",
       "      <td> 0.527603</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 0.469292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td> 0.862170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>      NaN</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>      NaN</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td>      NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td> 0.474422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td> 0.000782</td>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.033628</td>\n",
       "      <td>      NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2013-01-01  0.205240  0.527603  0.610052  0.469292\n",
       "2013-01-02  0.818113       NaN       NaN  0.862170\n",
       "2013-01-03       NaN  0.483201       NaN       NaN\n",
       "2013-01-04  0.719197       NaN  1.145788       NaN\n",
       "2013-01-05       NaN       NaN       NaN  0.474422\n",
       "2013-01-06  0.000782  0.146544  0.033628       NaN"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df > 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td>-0.534227</td>\n",
       "      <td>  two</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.161051</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td> 0.474422</td>\n",
       "      <td> four</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D     E\n",
       "2013-01-03 -1.462109  0.483201 -1.044973 -0.534227   two\n",
       "2013-01-05 -1.161051 -0.115774 -0.624413  0.474422  four"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# filtering\n",
    "df3 = df.copy()\n",
    "df3['E'] = ['one', 'one', 'two', 'three', 'four', 'three']\n",
    "df3[df3['E'].isin(['two', 'four'])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.161051</td>\n",
       "      <td>-0.115774</td>\n",
       "      <td>-0.624413</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td> 0.000782</td>\n",
       "      <td> 0.146544</td>\n",
       "      <td> 0.033628</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C  D\n",
       "2013-01-01  0.000000  0.000000  0.610052  5\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  5\n",
       "2013-01-03 -1.462109  0.483201 -1.044973  5\n",
       "2013-01-04  0.719197 -0.499809  1.145788  5\n",
       "2013-01-05 -1.161051 -0.115774 -0.624413  5\n",
       "2013-01-06  0.000782  0.146544  0.033628  5"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# setting examples\n",
    "df.at[dates[0],'A'] = 0\n",
    "df.iat[0,1] = 0\n",
    "df.loc[:, 'D'] = np.array([5] * len(df))\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 5</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 5</td>\n",
       "      <td>  1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td> 5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td> 5</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C  D   E\n",
       "2013-01-01  0.000000  0.000000  0.610052  5   1\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  5   1\n",
       "2013-01-03 -1.462109  0.483201 -1.044973  5 NaN\n",
       "2013-01-04  0.719197 -0.499809  1.145788  5 NaN"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# dealing with missing data\n",
    "df4 = df.reindex(index=dates[0:4],columns=list(df.columns) + ['E'])\n",
    "df4.loc[dates[0]:dates[1],'E'] = 1\n",
    "df4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.00000</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 5</td>\n",
       "      <td> 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.89439</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 5</td>\n",
       "      <td> 1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A        B         C  D  E\n",
       "2013-01-01  0.000000  0.00000  0.610052  5  1\n",
       "2013-01-02  0.818113 -0.89439 -1.602831  5  1"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# drop rows with missing data\n",
    "df4.dropna(how='any')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td> 5</td>\n",
       "      <td> 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-1.602831</td>\n",
       "      <td> 5</td>\n",
       "      <td> 1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-1.462109</td>\n",
       "      <td> 0.483201</td>\n",
       "      <td>-1.044973</td>\n",
       "      <td> 5</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.719197</td>\n",
       "      <td>-0.499809</td>\n",
       "      <td> 1.145788</td>\n",
       "      <td> 5</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C  D  E\n",
       "2013-01-01  0.000000  0.000000  0.610052  5  1\n",
       "2013-01-02  0.818113 -0.894390 -1.602831  5  1\n",
       "2013-01-03 -1.462109  0.483201 -1.044973  5  5\n",
       "2013-01-04  0.719197 -0.499809  1.145788  5  5"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# fill missing data\n",
    "df4.fillna(value=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td>  True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td> False</td>\n",
       "      <td>  True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                A      B      C      D      E\n",
       "2013-01-01  False  False  False  False  False\n",
       "2013-01-02  False  False  False  False  False\n",
       "2013-01-03  False  False  False  False   True\n",
       "2013-01-04  False  False  False  False   True"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# boolean mask for nan values\n",
    "pd.isnull(df4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A   -0.180845\n",
       "B   -0.146705\n",
       "C   -0.247125\n",
       "D    5.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2013-01-01    1.402513\n",
       "2013-01-02    0.830223\n",
       "2013-01-03    0.744030\n",
       "2013-01-04    1.591294\n",
       "2013-01-05    0.774691\n",
       "2013-01-06    1.295239\n",
       "Freq: D, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pivot the mean calculation\n",
    "df.mean(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-2.462109</td>\n",
       "      <td>-0.516799</td>\n",
       "      <td>-2.044973</td>\n",
       "      <td>  4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td>-2.280803</td>\n",
       "      <td>-3.499809</td>\n",
       "      <td>-1.854212</td>\n",
       "      <td>  2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-6.161051</td>\n",
       "      <td>-5.115774</td>\n",
       "      <td>-5.624413</td>\n",
       "      <td>  0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C   D\n",
       "2013-01-01       NaN       NaN       NaN NaN\n",
       "2013-01-02       NaN       NaN       NaN NaN\n",
       "2013-01-03 -2.462109 -0.516799 -2.044973   4\n",
       "2013-01-04 -2.280803 -3.499809 -1.854212   2\n",
       "2013-01-05 -6.161051 -5.115774 -5.624413   0\n",
       "2013-01-06       NaN       NaN       NaN NaN"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# aligning objects with different dimensions\n",
    "s = pd.Series([1,3,5,np.nan,6,8],index=dates).shift(2)\n",
    "df.sub(s,axis='index')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2013-01-01</th>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.000000</td>\n",
       "      <td> 0.610052</td>\n",
       "      <td>  5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-02</th>\n",
       "      <td> 0.818113</td>\n",
       "      <td>-0.894390</td>\n",
       "      <td>-0.992779</td>\n",
       "      <td> 10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-03</th>\n",
       "      <td>-0.643997</td>\n",
       "      <td>-0.411189</td>\n",
       "      <td>-2.037752</td>\n",
       "      <td> 15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-04</th>\n",
       "      <td> 0.075200</td>\n",
       "      <td>-0.910998</td>\n",
       "      <td>-0.891963</td>\n",
       "      <td> 20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-05</th>\n",
       "      <td>-1.085851</td>\n",
       "      <td>-1.026772</td>\n",
       "      <td>-1.516376</td>\n",
       "      <td> 25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-01-06</th>\n",
       "      <td>-1.085068</td>\n",
       "      <td>-0.880228</td>\n",
       "      <td>-1.482748</td>\n",
       "      <td> 30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C   D\n",
       "2013-01-01  0.000000  0.000000  0.610052   5\n",
       "2013-01-02  0.818113 -0.894390 -0.992779  10\n",
       "2013-01-03 -0.643997 -0.411189 -2.037752  15\n",
       "2013-01-04  0.075200 -0.910998 -0.891963  20\n",
       "2013-01-05 -1.085851 -1.026772 -1.516376  25\n",
       "2013-01-06 -1.085068 -0.880228 -1.482748  30"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# applying functions\n",
    "df.apply(np.cumsum)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    2.280222\n",
       "B    1.377591\n",
       "C    2.748619\n",
       "D    0.000000\n",
       "dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.apply(lambda x: x.max() - x.min())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4    3\n",
       "6    2\n",
       "1    2\n",
       "0    2\n",
       "5    1\n",
       "dtype: int64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# simple count aggregation\n",
    "s = pd.Series(np.random.randint(0,7,size=10))\n",
    "s.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Merging / Grouping / Shaping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.006589</td>\n",
       "      <td>-1.232048</td>\n",
       "      <td>-0.147323</td>\n",
       "      <td> 0.709050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-1.201048</td>\n",
       "      <td> 0.675688</td>\n",
       "      <td> 1.110037</td>\n",
       "      <td> 0.553489</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.159224</td>\n",
       "      <td>-1.226735</td>\n",
       "      <td>-0.141689</td>\n",
       "      <td>-1.450920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-0.049450</td>\n",
       "      <td>-0.438565</td>\n",
       "      <td> 0.670832</td>\n",
       "      <td> 1.089032</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.105969</td>\n",
       "      <td>-0.891644</td>\n",
       "      <td> 0.626482</td>\n",
       "      <td> 0.416679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>-1.103222</td>\n",
       "      <td>-1.983806</td>\n",
       "      <td> 0.282366</td>\n",
       "      <td> 0.031730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td> 0.380308</td>\n",
       "      <td>-0.397791</td>\n",
       "      <td>-0.322955</td>\n",
       "      <td> 0.074480</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>-0.623134</td>\n",
       "      <td>-0.205967</td>\n",
       "      <td>-0.367622</td>\n",
       "      <td> 1.437279</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>-0.481202</td>\n",
       "      <td> 1.242607</td>\n",
       "      <td>-2.107715</td>\n",
       "      <td> 1.020051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>-0.345859</td>\n",
       "      <td>-0.759047</td>\n",
       "      <td>-0.927940</td>\n",
       "      <td> 1.487916</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          0         1         2         3\n",
       "0 -0.006589 -1.232048 -0.147323  0.709050\n",
       "1 -1.201048  0.675688  1.110037  0.553489\n",
       "2 -0.159224 -1.226735 -0.141689 -1.450920\n",
       "3 -0.049450 -0.438565  0.670832  1.089032\n",
       "4 -0.105969 -0.891644  0.626482  0.416679\n",
       "5 -1.103222 -1.983806  0.282366  0.031730\n",
       "6  0.380308 -0.397791 -0.322955  0.074480\n",
       "7 -0.623134 -0.205967 -0.367622  1.437279\n",
       "8 -0.481202  1.242607 -2.107715  1.020051\n",
       "9 -0.345859 -0.759047 -0.927940  1.487916"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# concatenation\n",
    "df = pd.DataFrame(np.random.randn(10, 4))\n",
    "pieces = [df[:3], df[3:7], df[7:]]\n",
    "pd.concat(pieces)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>key</th>\n",
       "      <th>lval</th>\n",
       "      <th>rval</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td> foo</td>\n",
       "      <td> 1</td>\n",
       "      <td> 4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> foo</td>\n",
       "      <td> 1</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> foo</td>\n",
       "      <td> 2</td>\n",
       "      <td> 4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> foo</td>\n",
       "      <td> 2</td>\n",
       "      <td> 5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   key  lval  rval\n",
       "0  foo     1     4\n",
       "1  foo     1     5\n",
       "2  foo     2     4\n",
       "3  foo     2     5"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# SQL-style join\n",
    "left = pd.DataFrame({'key': ['foo', 'foo'], 'lval': [1, 2]})\n",
    "right = pd.DataFrame({'key': ['foo', 'foo'], 'rval': [4, 5]})\n",
    "pd.merge(left, right, on='key')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.992219</td>\n",
       "      <td> 1.298979</td>\n",
       "      <td> 0.998799</td>\n",
       "      <td>-0.164381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> 0.902147</td>\n",
       "      <td> 1.118289</td>\n",
       "      <td>-0.169358</td>\n",
       "      <td> 0.117833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> 1.201061</td>\n",
       "      <td>-1.699020</td>\n",
       "      <td>-2.112810</td>\n",
       "      <td>-1.412482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> 1.084910</td>\n",
       "      <td> 1.171135</td>\n",
       "      <td> 0.384876</td>\n",
       "      <td> 0.535239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.922543</td>\n",
       "      <td>-0.018670</td>\n",
       "      <td>-1.506012</td>\n",
       "      <td> 0.293739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td> 0.481017</td>\n",
       "      <td> 0.639182</td>\n",
       "      <td>-0.090676</td>\n",
       "      <td> 0.951261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td> 1.201241</td>\n",
       "      <td> 2.528836</td>\n",
       "      <td>-0.530795</td>\n",
       "      <td> 0.901950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td> 0.899290</td>\n",
       "      <td> 0.562738</td>\n",
       "      <td> 1.566468</td>\n",
       "      <td>-0.846827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td> 1.084910</td>\n",
       "      <td> 1.171135</td>\n",
       "      <td> 0.384876</td>\n",
       "      <td> 0.535239</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D\n",
       "0 -0.992219  1.298979  0.998799 -0.164381\n",
       "1  0.902147  1.118289 -0.169358  0.117833\n",
       "2  1.201061 -1.699020 -2.112810 -1.412482\n",
       "3  1.084910  1.171135  0.384876  0.535239\n",
       "4 -0.922543 -0.018670 -1.506012  0.293739\n",
       "5  0.481017  0.639182 -0.090676  0.951261\n",
       "6  1.201241  2.528836 -0.530795  0.901950\n",
       "7  0.899290  0.562738  1.566468 -0.846827\n",
       "8  1.084910  1.171135  0.384876  0.535239"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# append\n",
    "df = pd.DataFrame(np.random.randn(8, 4), columns=['A', 'B', 'C', 'D'])\n",
    "s = df.iloc[3]\n",
    "df.append(s, ignore_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td> foo</td>\n",
       "      <td>   one</td>\n",
       "      <td> 0.193948</td>\n",
       "      <td>-1.385614</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> bar</td>\n",
       "      <td>   one</td>\n",
       "      <td>-0.257859</td>\n",
       "      <td> 2.127808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> foo</td>\n",
       "      <td>   two</td>\n",
       "      <td>-0.944848</td>\n",
       "      <td>-0.760487</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> bar</td>\n",
       "      <td> three</td>\n",
       "      <td>-0.872161</td>\n",
       "      <td>-1.707254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td> foo</td>\n",
       "      <td>   two</td>\n",
       "      <td>-0.658552</td>\n",
       "      <td> 0.175699</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td> bar</td>\n",
       "      <td>   two</td>\n",
       "      <td>-1.887614</td>\n",
       "      <td> 0.627801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td> foo</td>\n",
       "      <td>   one</td>\n",
       "      <td> 0.439001</td>\n",
       "      <td>-2.264125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td> foo</td>\n",
       "      <td> three</td>\n",
       "      <td>-0.829368</td>\n",
       "      <td>-1.229315</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A      B         C         D\n",
       "0  foo    one  0.193948 -1.385614\n",
       "1  bar    one -0.257859  2.127808\n",
       "2  foo    two -0.944848 -0.760487\n",
       "3  bar  three -0.872161 -1.707254\n",
       "4  foo    two -0.658552  0.175699\n",
       "5  bar    two -1.887614  0.627801\n",
       "6  foo    one  0.439001 -2.264125\n",
       "7  foo  three -0.829368 -1.229315"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    { 'A' : ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],\n",
    "      'B' : ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'],\n",
    "      'C' : np.random.randn(8),\n",
    "      'D' : np.random.randn(8) })\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>bar</th>\n",
       "      <td>-3.017634</td>\n",
       "      <td> 1.048355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>foo</th>\n",
       "      <td>-1.799818</td>\n",
       "      <td>-5.463842</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            C         D\n",
       "A                      \n",
       "bar -3.017634  1.048355\n",
       "foo -1.799818 -5.463842"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group by\n",
    "df.groupby('A').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">bar</th>\n",
       "      <th>one</th>\n",
       "      <td>-0.257859</td>\n",
       "      <td> 2.127808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>-0.872161</td>\n",
       "      <td>-1.707254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>-1.887614</td>\n",
       "      <td> 0.627801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">foo</th>\n",
       "      <th>one</th>\n",
       "      <td> 0.632949</td>\n",
       "      <td>-3.649739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>three</th>\n",
       "      <td>-0.829368</td>\n",
       "      <td>-1.229315</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>two</th>\n",
       "      <td>-1.603400</td>\n",
       "      <td>-0.584788</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  C         D\n",
       "A   B                        \n",
       "bar one   -0.257859  2.127808\n",
       "    three -0.872161 -1.707254\n",
       "    two   -1.887614  0.627801\n",
       "foo one    0.632949 -3.649739\n",
       "    three -0.829368 -1.229315\n",
       "    two   -1.603400 -0.584788"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# group by multiple columns\n",
    "df.groupby(['A','B']).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>E</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0 </th>\n",
       "      <td>   one</td>\n",
       "      <td> A</td>\n",
       "      <td> foo</td>\n",
       "      <td>-0.853288</td>\n",
       "      <td> 2.549878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1 </th>\n",
       "      <td>   one</td>\n",
       "      <td> B</td>\n",
       "      <td> foo</td>\n",
       "      <td> 0.552557</td>\n",
       "      <td> 0.865465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2 </th>\n",
       "      <td>   two</td>\n",
       "      <td> C</td>\n",
       "      <td> foo</td>\n",
       "      <td> 0.700943</td>\n",
       "      <td> 0.800563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3 </th>\n",
       "      <td> three</td>\n",
       "      <td> A</td>\n",
       "      <td> bar</td>\n",
       "      <td>-0.466072</td>\n",
       "      <td> 0.011508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4 </th>\n",
       "      <td>   one</td>\n",
       "      <td> B</td>\n",
       "      <td> bar</td>\n",
       "      <td> 0.465724</td>\n",
       "      <td> 1.087874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5 </th>\n",
       "      <td>   one</td>\n",
       "      <td> C</td>\n",
       "      <td> bar</td>\n",
       "      <td> 1.105949</td>\n",
       "      <td>-0.118134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6 </th>\n",
       "      <td>   two</td>\n",
       "      <td> A</td>\n",
       "      <td> foo</td>\n",
       "      <td>-0.666630</td>\n",
       "      <td>-0.143474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7 </th>\n",
       "      <td> three</td>\n",
       "      <td> B</td>\n",
       "      <td> foo</td>\n",
       "      <td> 0.644902</td>\n",
       "      <td> 1.731818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8 </th>\n",
       "      <td>   one</td>\n",
       "      <td> C</td>\n",
       "      <td> foo</td>\n",
       "      <td> 0.819170</td>\n",
       "      <td>-1.153036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9 </th>\n",
       "      <td>   one</td>\n",
       "      <td> A</td>\n",
       "      <td> bar</td>\n",
       "      <td>-1.849893</td>\n",
       "      <td> 0.733137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>   two</td>\n",
       "      <td> B</td>\n",
       "      <td> bar</td>\n",
       "      <td> 0.684170</td>\n",
       "      <td>-0.276237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td> three</td>\n",
       "      <td> C</td>\n",
       "      <td> bar</td>\n",
       "      <td> 0.592939</td>\n",
       "      <td>-0.830433</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        A  B    C         D         E\n",
       "0     one  A  foo -0.853288  2.549878\n",
       "1     one  B  foo  0.552557  0.865465\n",
       "2     two  C  foo  0.700943  0.800563\n",
       "3   three  A  bar -0.466072  0.011508\n",
       "4     one  B  bar  0.465724  1.087874\n",
       "5     one  C  bar  1.105949 -0.118134\n",
       "6     two  A  foo -0.666630 -0.143474\n",
       "7   three  B  foo  0.644902  1.731818\n",
       "8     one  C  foo  0.819170 -1.153036\n",
       "9     one  A  bar -1.849893  0.733137\n",
       "10    two  B  bar  0.684170 -0.276237\n",
       "11  three  C  bar  0.592939 -0.830433"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.DataFrame(\n",
    "    { 'A' : ['one', 'one', 'two', 'three'] * 3,\n",
    "      'B' : ['A', 'B', 'C'] * 4,\n",
    "      'C' : ['foo', 'foo', 'foo', 'bar', 'bar', 'bar'] * 2,\n",
    "      'D' : np.random.randn(12),\n",
    "      'E' : np.random.randn(12)} )\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Program Files\\Anaconda\\lib\\site-packages\\pandas\\util\\decorators.py:53: FutureWarning: rows is deprecated, use index instead\n",
      "  warnings.warn(msg, FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>C</th>\n",
       "      <th>bar</th>\n",
       "      <th>foo</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">one</th>\n",
       "      <th>A</th>\n",
       "      <td>-1.849893</td>\n",
       "      <td>-0.853288</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td> 0.465724</td>\n",
       "      <td> 0.552557</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td> 1.105949</td>\n",
       "      <td> 0.819170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">three</th>\n",
       "      <th>A</th>\n",
       "      <td>-0.466072</td>\n",
       "      <td>      NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td>      NaN</td>\n",
       "      <td> 0.644902</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td> 0.592939</td>\n",
       "      <td>      NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">two</th>\n",
       "      <th>A</th>\n",
       "      <td>      NaN</td>\n",
       "      <td>-0.666630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>B</th>\n",
       "      <td> 0.684170</td>\n",
       "      <td>      NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>C</th>\n",
       "      <td>      NaN</td>\n",
       "      <td> 0.700943</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "C             bar       foo\n",
       "A     B                    \n",
       "one   A -1.849893 -0.853288\n",
       "      B  0.465724  0.552557\n",
       "      C  1.105949  0.819170\n",
       "three A -0.466072       NaN\n",
       "      B       NaN  0.644902\n",
       "      C  0.592939       NaN\n",
       "two   A       NaN -0.666630\n",
       "      B  0.684170       NaN\n",
       "      C       NaN  0.700943"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pivot table\n",
    "pd.pivot_table(df, values='D', rows=['A', 'B'], columns=['C'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Time Series"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2012-01-01    24406\n",
       "Freq: 5T, dtype: int32"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# time period resampling\n",
    "rng = pd.date_range('1/1/2012', periods=100, freq='S')\n",
    "ts = pd.Series(np.random.randint(0, 500, len(rng)), index=rng)\n",
    "ts.resample('5Min', how='sum')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2012-01-31   -0.624893\n",
       "2012-02-29   -0.176292\n",
       "2012-03-31    1.673556\n",
       "2012-04-30    0.707903\n",
       "2012-05-31    0.533647\n",
       "Freq: M, dtype: float64"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rng = pd.date_range('1/1/2012', periods=5, freq='M')\n",
    "ts = pd.Series(np.random.randn(len(rng)), index=rng)\n",
    "ts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2012-01-01   -0.624893\n",
       "2012-02-01   -0.176292\n",
       "2012-03-01    1.673556\n",
       "2012-04-01    0.707903\n",
       "2012-05-01    0.533647\n",
       "Freq: MS, dtype: float64"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ps = ts.to_period()\n",
    "ps.to_timestamp()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0xd180438>"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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       "C4IgpAki0AVBENKE/w/D/Ob0kyuqAwAAAABJRU5ErkJggg==\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd0ceb70>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# time series plot\n",
    "ts = pd.Series(np.random.randn(1000), index=pd.date_range('1/1/2000', periods=1000))\n",
    "ts = ts.cumsum()\n",
    "ts.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0xd541fd0>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd554550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "1BO0QddoNJp6gjboGo1GU0/4fw9A8R8bklIsAAAAAElFTkSuQmCC\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0xd541cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot with a data frame\n",
    "df = pd.DataFrame(np.random.randn(1000, 4), index=ts.index, columns=['A', 'B', 'C', 'D'])\n",
    "df = df.cumsum()\n",
    "plt.figure(); df.plot(); plt.legend(loc='best')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Input / Output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# write to a csv file\n",
    "df.to_csv('foo.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-0.914956</td>\n",
       "      <td> 0.294759</td>\n",
       "      <td> 0.143332</td>\n",
       "      <td> 0.174706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.297442</td>\n",
       "      <td> 1.640208</td>\n",
       "      <td> 0.425301</td>\n",
       "      <td>-0.075666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.762292</td>\n",
       "      <td> 0.741179</td>\n",
       "      <td> 0.505002</td>\n",
       "      <td>-0.128560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>-1.577471</td>\n",
       "      <td>-0.495294</td>\n",
       "      <td> 1.803332</td>\n",
       "      <td> 0.188178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-0.137486</td>\n",
       "      <td>-0.676985</td>\n",
       "      <td> 1.435308</td>\n",
       "      <td> 0.181047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          A         B         C         D\n",
       "0 -0.914956  0.294759  0.143332  0.174706\n",
       "1 -0.297442  1.640208  0.425301 -0.075666\n",
       "2 -0.762292  0.741179  0.505002 -0.128560\n",
       "3 -1.577471 -0.495294  1.803332  0.188178\n",
       "4 -0.137486 -0.676985  1.435308  0.181047"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# read file back in\n",
    "path = r'C:\\Users\\John\\Documents\\IPython Notebooks\\foo.csv'\n",
    "newDf = pd.read_csv(path)\n",
    "newDf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# remove the file\n",
    "import os\n",
    "os.remove(path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# can also do Excel\n",
    "df.to_excel('foo.xlsx', sheet_name='Sheet1')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2000-01-01</th>\n",
       "      <td>-0.914956</td>\n",
       "      <td> 0.294759</td>\n",
       "      <td> 0.143332</td>\n",
       "      <td> 0.174706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-02</th>\n",
       "      <td>-0.297442</td>\n",
       "      <td> 1.640208</td>\n",
       "      <td> 0.425301</td>\n",
       "      <td>-0.075666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-03</th>\n",
       "      <td>-0.762292</td>\n",
       "      <td> 0.741179</td>\n",
       "      <td> 0.505002</td>\n",
       "      <td>-0.128560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-04</th>\n",
       "      <td>-1.577471</td>\n",
       "      <td>-0.495294</td>\n",
       "      <td> 1.803332</td>\n",
       "      <td> 0.188178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-05</th>\n",
       "      <td>-0.137486</td>\n",
       "      <td>-0.676985</td>\n",
       "      <td> 1.435308</td>\n",
       "      <td> 0.181047</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   A         B         C         D\n",
       "2000-01-01 -0.914956  0.294759  0.143332  0.174706\n",
       "2000-01-02 -0.297442  1.640208  0.425301 -0.075666\n",
       "2000-01-03 -0.762292  0.741179  0.505002 -0.128560\n",
       "2000-01-04 -1.577471 -0.495294  1.803332  0.188178\n",
       "2000-01-05 -0.137486 -0.676985  1.435308  0.181047"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "newDf2 = pd.read_excel('foo.xlsx', 'Sheet1', index_col=None, na_values=['NA'])\n",
    "newDf2.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "os.remove('foo.xlsx')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.9"
  }
 },
 "nbformat": 4,
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}