{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Module 7\n", "\n", "## Video 31: Floating Storage\n", "**Python for the Energy Industry**\n", "\n", "One use of the CargoTimeSeries endpoint is to study how floating storage levels change over time. We start with our usual setup:\n", "\n", "[Cargo Time Series documentation.](https://vortechsa.github.io/python-sdk/endpoints/cargo_timeseries/)\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "# initial imports\n", "import pandas as pd\n", "import numpy as np\n", "from datetime import datetime\n", "from dateutil.relativedelta import relativedelta\n", "import vortexasdk as v\n", "\n", "# The cargo unit for the time series (barrels)\n", "TS_UNIT = 'b'\n", "\n", "# The granularity of the time series\n", "TS_FREQ = 'day'\n", "\n", "# datetimes to access last 7 weeks of data\n", "now = datetime.utcnow()\n", "seven_weeks_ago = now - relativedelta(weeks=7)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's look at how global levels of floating storage of crude have varied over the last 7 weeks. There will be enough data to look at variation on a daily basis. We also add a requirement to only include floating storage that lasted longer than 14 days.\n", "\n", "*Note: a cargo is defined by Vortexa as becoming floating storage after it has been stationary for 7 days with no STS transfers. So a cargo that has been in floating storage for 14 days has been stationary for 21 days. 'Long-term' floating storage is FS for > 30 days.*" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "# Find crude ID\n", "crude = [p.id for p in v.Products().search('crude').to_list() if p.name=='Crude']\n", "assert len(crude) == 1\n", "\n", "search_result = v.CargoTimeSeries().search(\n", " timeseries_frequency=TS_FREQ,\n", " timeseries_unit=TS_UNIT,\n", " filter_products=crude,\n", " filter_time_min=seven_weeks_ago,\n", " filter_time_max=now,\n", " # Filter for cargo in floating storage\n", " filter_activity=\"storing_state\",\n", " # Only get floating storage that lasted longer than 21 days\n", " timeseries_activity_time_span_min=1000 * 60 * 60 * 24 * 14,\n", ")\n", "\n", "df_floating_storage = search_result.to_df()\n", "\n", "df_floating_storage = df_floating_storage.rename(columns = {'key': 'date', 'value': 'barrels'})" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datebarrelscount
02020-10-23 00:00:00+00:005330449191
12020-10-24 00:00:00+00:005520262093
22020-10-25 00:00:00+00:005753719296
32020-10-26 00:00:00+00:006136549699
42020-10-27 00:00:00+00:0066680069111
\n", "
" ], "text/plain": [ " date barrels count\n", "0 2020-10-23 00:00:00+00:00 53304491 91\n", "1 2020-10-24 00:00:00+00:00 55202620 93\n", "2 2020-10-25 00:00:00+00:00 57537192 96\n", "3 2020-10-26 00:00:00+00:00 61365496 99\n", "4 2020-10-27 00:00:00+00:00 66680069 111" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_floating_storage.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can make a plot of how the total quantity in barrels varies over time:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'floating storage (barrels)')" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = df_floating_storage.plot(x='date',y='barrels',legend=False,figsize=(8,4))\n", "ax.set_ylabel('floating storage (barrels)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's say we now want to compare the time variation of floating storage of each category of crude. To do this, we can loop over each category and do a separate search that filters on that category only.\n", "\n", "To start, we get the IDs of each category of crude:" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "medium_sour = [p.id for p in v.Products().search('medium-sour').to_list() if p.name=='Medium-Sour']\n", "light_sour = [p.id for p in v.Products().search('light-sour').to_list() if p.name=='Light-Sour']\n", "heavy_sour = [p.id for p in v.Products().search('heavy-sour').to_list() if p.name=='Heavy-Sour']\n", "medium_sweet = [p.id for p in v.Products().search('medium-sweet').to_list() if p.name=='Medium-Sweet']\n", "light_sweet = [p.id for p in v.Products().search('light-sweet').to_list() if p.name=='Light-Sweet']\n", "heavy_sweet = [p.id for p in v.Products().search('heavy-sweet').to_list() if p.name=='Heavy-Sweet']\n", "\n", "assert len(medium_sour) == 1\n", "assert len(light_sour) == 1\n", "assert len(heavy_sour) == 1\n", "assert len(medium_sweet) == 1\n", "assert len(light_sweet) == 1\n", "assert len(heavy_sweet) == 1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "To make these more convenient to work with, we make a dictionary for the ID of each category:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "crude_dict = {\n", " 'medium-sour': medium_sour[0],\n", " 'light-sour': light_sour[0],\n", " 'heavy-sour': heavy_sour[0],\n", " 'medium-sweet': medium_sweet[0],\n", " 'light-sweet': light_sweet[0],\n", " 'heavy-sweet': heavy_sweet[0],\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We then do a loop over the categories in the dictionary. For each search, we produce a DataFrame, and then add the `values` column to our `df_floating_storage` DataFrame. " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "for category in crude_dict:\n", " search_result = v.CargoTimeSeries().search(\n", " timeseries_frequency=TS_FREQ,\n", " timeseries_unit=TS_UNIT,\n", " # filter only on one category of crude\n", " filter_products=crude_dict[category],\n", " filter_time_min=seven_weeks_ago,\n", " filter_time_max=now,\n", " # Filter for cargo in floating storage\n", " filter_activity=\"storing_state\",\n", " # Only get floating storage that lasted longer than 21 days\n", " timeseries_activity_time_span_min=1000 * 60 * 60 * 24 * 14,\n", " )\n", "\n", " df_cat = search_result.to_df()\n", " df_floating_storage[category] = df_cat['value']" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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datebarrelscountmedium-sourlight-sourheavy-sourmedium-sweetlight-sweetheavy-sweet
02020-10-23 00:00:00+00:0053304491911433253246010117293267888304034902632882745
12020-10-24 00:00:00+00:0055202620931621990646010117293267888304034902632882745
22020-10-25 00:00:00+00:0057537192961855447846010117293267888304034902632882745
32020-10-26 00:00:00+00:0061365496991919479251771067293267920692125822433778060
42020-10-27 00:00:00+00:006668006911121153328517710670448901172755438485093778060
\n", "
" ], "text/plain": [ " date barrels count medium-sour light-sour \\\n", "0 2020-10-23 00:00:00+00:00 53304491 91 14332532 4601011 \n", "1 2020-10-24 00:00:00+00:00 55202620 93 16219906 4601011 \n", "2 2020-10-25 00:00:00+00:00 57537192 96 18554478 4601011 \n", "3 2020-10-26 00:00:00+00:00 61365496 99 19194792 5177106 \n", "4 2020-10-27 00:00:00+00:00 66680069 111 21153328 5177106 \n", "\n", " heavy-sour medium-sweet light-sweet heavy-sweet \n", "0 7293267 8883040 3490263 2882745 \n", "1 7293267 8883040 3490263 2882745 \n", "2 7293267 8883040 3490263 2882745 \n", "3 7293267 9206921 2582243 3778060 \n", "4 7044890 11727554 3848509 3778060 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_floating_storage.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We now have the data we need to make a plot comparing each of these categories:" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'floating storage (barrels)')" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ax = df_floating_storage.plot(x='date',y=list(crude_dict.keys()),figsize=(8,4))\n", "ax.set_ylabel('floating storage (barrels)')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Exercise\n", "\n", "Compare and plot the floating storage of crude in different geographic regions over the last 7 weeks." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" } }, "nbformat": 4, "nbformat_minor": 4 }