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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Try out the VortexaSDK"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First let's import our requirements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T11:17:13.956707Z",
     "iopub.status.busy": "2024-04-05T11:17:13.956131Z",
     "iopub.status.idle": "2024-04-05T11:17:14.344989Z",
     "shell.execute_reply": "2024-04-05T11:17:14.344587Z"
    }
   },
   "outputs": [],
   "source": [
    "from datetime import datetime, timedelta, time\n",
    "import vortexasdk as v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets use the CanalTransitTimeseries endpoint to answer the following question:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-  _What was the number of vessels waiting to enter Panama Canal yesterday_?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T11:17:14.347598Z",
     "iopub.status.busy": "2024-04-05T11:17:14.347390Z",
     "iopub.status.idle": "2024-04-05T11:17:14.532165Z",
     "shell.execute_reply": "2024-04-05T11:17:14.531550Z"
    }
   },
   "outputs": [],
   "source": [
    "search_result = v.CanalTransitTimeseries().search(\n",
    "        metric=\"count_of_vessels\",\n",
    "        timeseries_frequency=\"day\",\n",
    "        time_max=datetime.combine(datetime.now(), time.max),\n",
    "        time_min=datetime.combine(datetime.now() - timedelta(days=1), time.min),\n",
    "        timeseries_activity=\"started_waiting\"\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T11:17:14.535683Z",
     "iopub.status.busy": "2024-04-05T11:17:14.535437Z",
     "iopub.status.idle": "2024-04-05T11:17:15.059448Z",
     "shell.execute_reply": "2024-04-05T11:17:15.058756Z"
    }
   },
   "outputs": [],
   "source": [
    "df = search_result.to_df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-05T11:17:15.062252Z",
     "iopub.status.busy": "2024-04-05T11:17:15.062063Z",
     "iopub.status.idle": "2024-04-05T11:17:15.073400Z",
     "shell.execute_reply": "2024-04-05T11:17:15.073014Z"
    }
   },
   "outputs": [],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's it! You've successfully loaded data using the Vortexa SDK. Check out https://vortechsa.github.io/python-sdk/ for more examples"
   ]
  }
 ],
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