updating

src/Intensivstationen.ipynb

@@ -0,0 +1,101 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "9de5907f-18f5-4cb1-903e-26028ff1fa03",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "pd.set_option('display.max_rows', 100)\n",
+    "pd.set_option('display.max_columns', None)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "997a4bdb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def readTimeseries(bundesland = None):\n",
+    "    df = pd.read_csv(\n",
+    "        'intensivstationen/zeitreihe-bundeslaender.csv',\n",
+    "        low_memory = False,\n",
+    "        parse_dates = ['Datum'],\n",
+    "        date_parser = lambda dateStr: pd.to_datetime(dateStr, utc = True))\n",
+    "    if bundesland is not None:\n",
+    "        return df[df['Bundesland'] == bundesland][['Datum', 'Belegte_Intensivbetten', 'Freie_Intensivbetten', '7_Tage_Notfallreserve']]\n",
+    "    else:\n",
+    "        res = df.groupby('Datum').agg(**{\n",
+    "                        'Belegte_Intensivbetten': pd.NamedAgg(column = 'Belegte_Intensivbetten', aggfunc = 'sum'),\n",
+    "                        'Freie_Intensivbetten':   pd.NamedAgg(column = 'Freie_Intensivbetten',   aggfunc = 'sum'),\n",
+    "                        '7_Tage_Notfallreserve':  pd.NamedAgg(column = '7_Tage_Notfallreserve',  aggfunc = 'sum'), \n",
+    "                    })\n",
+    "        #df = df[['Datum', 'Belegte_Intensivbetten', 'Freie_Intensivbetten', '7_Tage_Notfallreserve']]\n",
+    "        #res.to_csv('../docs/data/intensivstationen/data-de-generated.csv', index = True)\n",
+    "        return res.reset_index()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a97f5b2b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def readAndPersistTimeseries(bundesland = None):\n",
+    "    dataFrame = readTimeseries(bundesland)\n",
+    "    dataFrame.to_csv(_getFilename(bundesland), index =False)\n",
+    "    return dataFrame\n",
+    "\n",
+    "def _getFilename(bundesland):\n",
+    "    return '../docs/data/intensivstationen/intensivstationen{suffix}.csv'.format(suffix = '-' + bundesland if bundesland is not None else '-de')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63ca93a4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "readAndPersistTimeseries(bundesland = 'BADEN_WUERTTEMBERG')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "349edd73",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "readAndPersistTimeseries()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}