docs/examples/try_me_out/utilisation_capacity_timeseries.ipynb

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  {
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   "source": [
    "### Try out the VortexaSDK"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First let's import our requirements"
   ]
  },
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   "source": [
    "from datetime import datetime\n",
    "import vortexasdk as v"
   ]
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ton days supply (ballast) of vessels originating from the Middle East by daily frequency over the last 7 days, by `origin_country` breakdown."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You'll need to enter your Vortexa API key when prompted."
   ]
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   "source": [
    "df = v.FleetUtilisationCapacityTimeseries().search(\n",
    "    filter_vessel_status=\"vessel_status_ballast\",\n",
    "    filter_time_min=datetime(2021, 1, 11),\n",
    "    filter_time_max=datetime(2021, 1, 18),\n",
    "    timeseries_frequency=\"day\",\n",
    "    filter_origins=\"80aa9e4f3014c3d96559c8e642157edbb2b684ea0144ed76cd20b3af75110877\",\n",
    "    timeseries_property=\"origin_country\"\n",
    ").to_df()"
   ]
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    "execution": {
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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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