{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "text/markdown": [ "[Execute this notebook with Binder](https://mybinder.org/v2/gh/oscovida/binder/master?filepath=ipynb/tutorial-overview-plot_daily_change.ipynb)" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "%config InlineBackend.figure_formats = ['svg']\n", "import oscovida as ov\n", "\n", "ov.display_binder_link(\"tutorial-overview-plot_daily_change.ipynb\")" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Daily change\n", "\n", "The second and the third graphs returned by the `overview` function \n", "(see the [overview](tutorial-overview-graphs.nbdata.html)\n", "and the explanation of the [observables](tutorial-observables.nbdata.html))\n", "show the daily changes for COVID cases and deaths respectively. Here we show how it is created internally.\n", "We also meed to import the plotting framework:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "from matplotlib.dates import DateFormatter, MONDAY, WeekdayLocator, DayLocator" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Also we will need an empty Matplotlib graph object to pass onto the plotting functions." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n" ], "text/plain": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig2, ax2 = plt.subplots(); # create an empty graph\n", "country = \"US\"\n", "region = \"California\"\n", "weeks = 8\n", "\n", "cases, deaths = ov.get_country_data(country, region) # get actual data\n", "cases = cases[- weeks * 7:] # cut off unwanted data\n", "\n", "# pass the data to the plotting function\n", "ov.plot_daily_change(ax=ax2, series=cases, labels=(\"USA: California\",\"cases\"), color=\"C2\", \n", " country=\"US\", region=\"California\");\n", "\n", "# nicer X-axis formatting: put a tick every Monday\n", "ax2.get_xaxis().set_major_locator(WeekdayLocator(byweekday=MONDAY)) \n", "ax2.get_xaxis().set_major_formatter(DateFormatter('%d %b'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And if it we wave the population data for this region (see [here](link-here))\n", "then we can plot a normalised graph with the data per 100K capita.\n", "For doing that we pass regional identifiers to the plotting function. And here we will use deaths data:" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "pycharm": { "name": "#%%\n" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The population of Germany, Bayern is 13124737 people\n" ] }, { "data": { "image/svg+xml": [ "\n", "\n", "\n", "\n" ], "text/plain": [ "

" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig2, ax2 = plt.subplots(); # an empty graph again\n", "country = \"Germany\"\n", "region = \"Bayern\"\n", "weeks = 8\n", "\n", "cases, deaths = ov.get_country_data(country, region)\n", "dates = \"2020-05-01:2020-07-15\"\n", "date_start, date_end = dates.split(':')\n", "deaths = deaths[date_start: date_end] # cut off unwanted data\n", "\n", "habitants = ov.population(country, region)\n", "print(f\"The population of {country}, {region} is {habitants} people\")\n", "\n", "ov.plot_daily_change(ax=ax2, series=deaths, color=\"C2\", labels=(\"Germany: Bavaria\", \"deaths\"), \n", " country=country, region=region);\n", "\n", "# nicer X-axis formatting: put a tick every Monday\n", "ax2.get_xaxis().set_major_locator(DayLocator(bymonthday=1)) \n", "ax2.get_xaxis().set_major_formatter(DateFormatter('%d %b'))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Other tutorials\n", "\n", "You can find [more tutorials here](tag-tutorial.html)." ] }, { "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": "3.7.7" } }, "nbformat": 4, "nbformat_minor": 4 }