docs/examples/try_me_out/cargo_timeseries.ipynb

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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",
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   "source": [
    "from datetime import datetime\n",
    "import vortexasdk as v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets use the CargoTimeSeries endpoint to answer the following question:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-  _What was the monthly average barrels per day of crude loaded from Rotterdam over the last year_?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we'll find the IDs corresponding to Rotterdam and Crude"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "execution": {
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   "outputs": [],
   "source": [
    "rotterdam = [g.id for g in v.Geographies().search(\"Rotterdam\", exact_term_match=True).to_list()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "execution": {
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   "source": [
    "crude = [p.id for p in v.Products().search(\"Crude\", exact_term_match=True).to_list()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2020-12-29T16:41:54.624361Z"
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   },
   "outputs": [],
   "source": [
    "search_result = v.CargoTimeSeries().search(\n",
    "    timeseries_unit='bpd',\n",
    "    timeseries_frequency='month',\n",
    "    filter_origins=rotterdam,\n",
    "    filter_products=crude,\n",
    "    filter_activity='loading_state',\n",
    "    filter_time_min=datetime(2018, 1, 1),\n",
    "    filter_time_max=datetime(2018, 12, 31))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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    "execution": {
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     "shell.execute_reply": "2020-12-29T16:41:54.634132Z"
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   },
   "outputs": [],
   "source": [
    "df = search_result.to_df()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2020-12-29T16:41:54.644182Z",
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     "shell.execute_reply": "2020-12-29T16:41:54.654072Z"
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   },
   "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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