docs/examples/try_me_out/utilisation_avg_distance_timeseries.ipynb

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   "source": [
    "### Try out the VortexaSDK"
   ]
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  {
   "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": [
    "Average distance traveled per day, by laden vessels between Middle East and China, in nautical miles."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You'll need to enter your Vortexa API key when prompted."
   ]
  },
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   "source": [
    "df = v.FleetUtilisationAvgDistanceTimeseries().search(\n",
    "    filter_vessel_status=\"vessel_status_laden_known\",\n",
    "    filter_time_min=datetime(2021, 1, 11),\n",
    "    filter_time_max=datetime(2021, 1, 18),\n",
    "    filter_origins=\"80aa9e4f3014c3d96559c8e642157edbb2b684ea0144ed76cd20b3af75110877\",\n",
    "    filter_destinations=\"934c47f36c16a58d68ef5e007e62a23f5f036ee3f3d1f5f85a48c572b90ad8b2\",\n",
    "    timeseries_property=\"quantity\",\n",
    "    timeseries_frequency=\"day\",\n",
    "    timeseries_unit=\"nmi\"\n",
    ").to_df()"
   ]
  },
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   "cell_type": "code",
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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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