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frankknoll
2022-03-20 18:42:56 +01:00
parent 21138394ec 720a94240c
commit cde8b62338
9 changed files with 1797 additions and 80 deletions
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8
src/HowBadIsMyBatch.ipynb
View File

@@ -806,14 +806,6 @@
" country = 'Global',\n",
" minADRsForLethality = minADRsForLethality)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9c70f2db",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {

28
src/help.txt
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@@ -15,32 +15,12 @@ get VAERS data:
- download data (e.g. 2022VAERSData.zip) from https://vaers.hhs.gov/data/datasets.html and save and unzip in VAERS folder
FK-FIXME:
- Fcron funktioniert nicht, jobs werden im Nachhinein nicht ausgeführt, verwende Autocron statt Fcron
FK-TODO:
- Format des jeweiligen Herstellers berücksichtigen:
039k20a
MOD039K20A
#039K20A
039K20A-MODERNA
039K20A-2A (vielleicht nicht)
039K20A or 039L
Moderna/039K20A
MODERNA 039K20A
MODERNA039K20A
Modena 039k20A
L039K20A
M039K20A
MOD; 039K20A
m0039k20A
u039k20a
6/21 039K20A
2039K20A
013L20A 039K20A#039K20A
#039K
039K20A 12-31-
039K20A & 031M2
039K20A and 032
039K20A, 011L20
- Darstellung als Dashboard, siehe https://covid-karte.de/ oder https://experience.arcgis.com/experience/3a132983ad3c4ab8a28704e9addefaba
- Rot-Gelb-Grün eingefärbte Deutschland-Karte anzeigen wie in https://experience.arcgis.com/experience/3a132983ad3c4ab8a28704e9addefaba
- Alle Charts mit Slidern versehen?
man 5 fcrontab

139
src/intensivstationen/Intensivstationen.ipynb
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@@ -838,6 +838,30 @@
" return BeautifulSoup(html, 'lxml')\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "29b0930a",
"metadata": {},
"outputs": [],
"source": [
"import unittest"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "45072a1d",
"metadata": {},
"outputs": [],
"source": [
"class TestHelper:\n",
"\n",
" @staticmethod\n",
" def createDataFrame(index, columns, data, dtypes = {}):\n",
" return pd.DataFrame(index = index, columns = columns, data = data).astype(dtypes)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -845,9 +869,6 @@
"metadata": {},
"outputs": [],
"source": [
"import unittest\n",
"\n",
"\n",
"class KreisOptionsSetterTest(unittest.TestCase):\n",
"\n",
" def test_setKreisOptions(self):\n",
@@ -856,7 +877,7 @@
"\n",
" # When\n",
" htmlActual = kreisOptionsSetter.setKreisOptions(\n",
" html = '''\n",
" html='''\n",
" <html>\n",
" <body>\n",
" <p>Test<p/>\n",
@@ -869,7 +890,7 @@
" </body>\n",
" </html>\n",
" ''',\n",
" options = [\n",
" options=[\n",
" '<option selected=\"\" value=\"de\">Alle Landkreise</option>',\n",
" '<option value=\"Ahrweiler\">Ahrweiler</option>',\n",
" '<option value=\"Aichach-Friedberg\">Aichach-Friedberg</option>'])\n",
@@ -891,6 +912,8 @@
" ''')\n",
"\n",
"# adapted from https://stackoverflow.com/questions/8006909/pretty-print-assertequal-for-html-strings\n",
"\n",
"\n",
"def assertEqualHTML(string1, string2, file1='', file2=''):\n",
" u'''\n",
" Compare two unicode strings containing HTML.\n",
@@ -920,16 +943,6 @@
" raise Exception('Not equal %s %s' % (file1, file2))\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e80117e5",
"metadata": {},
"outputs": [],
"source": [
"unittest.main(argv = [''], verbosity = 2, exit = False)"
]
},
{
"cell_type": "code",
"execution_count": null,
@@ -1359,6 +1372,7 @@
"outputs": [],
"source": [
"import os\n",
"import json\n",
"\n",
"\n",
"class IOUtils:\n",
@@ -1389,7 +1403,7 @@
" return timeSeries.groupby('date').agg(**{\n",
" 'betten_belegt': pd.NamedAgg(column = 'betten_belegt', aggfunc = 'sum'),\n",
" 'betten_frei': pd.NamedAgg(column = 'betten_frei', aggfunc = 'sum'),\n",
" 'Einwohnerzahl': pd.NamedAgg(column = 'Einwohnerzahl', aggfunc = 'sum') \n",
" 'Einwohnerzahl': pd.NamedAgg(column = 'Einwohnerzahl', aggfunc = 'sum')\n",
" }).reset_index()"
]
},
@@ -1400,9 +1414,6 @@
"metadata": {},
"outputs": [],
"source": [
"import json\n",
"\n",
"\n",
"def getAndPersistIntensiveCareBeds(timeSeries, kreis = None):\n",
" intensiveCareBeds = getIntensiveCareBeds(timeSeries, kreis)\n",
" display(kreis)\n",
@@ -5052,6 +5063,96 @@
" getAndPersistIntensiveCareBeds(timeSeries, kreis)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d9d4acab",
"metadata": {},
"outputs": [],
"source": [
"class MedianOfFreeBedsByKreisTableFactory:\n",
" \n",
" def __init__(self, dataFrame):\n",
" self.dataFrame = dataFrame\n",
"\n",
" def createMedianOfFreeBedsByKreisTable(self):\n",
" self.dataFrame['free_beds_divided_by_all_beds_in_percent'] = self.dataFrame['betten_frei'] / (self.dataFrame['betten_frei'] + self.dataFrame['betten_belegt']) * 100\n",
" aggregated = self.dataFrame.groupby('Kreis').agg(\n",
" median_free_beds_in_percent =\n",
" pd.NamedAgg(\n",
" column = 'free_beds_divided_by_all_beds_in_percent',\n",
" aggfunc = 'median'))\n",
" return aggregated.sort_values(by = 'median_free_beds_in_percent', ascending = False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a739d4d1",
"metadata": {},
"outputs": [],
"source": [
"from pandas.testing import assert_frame_equal\n",
"import statistics\n",
"\n",
"class MedianOfFreeBedsByKreisTableFactoryTest(unittest.TestCase):\n",
"\n",
" def test_createMedianOfFreeBedsByKreisTable(self):\n",
" # Given\n",
" dataFrame = TestHelper.createDataFrame(\n",
" columns = ['date', 'betten_frei', 'betten_belegt', 'Kreis'],\n",
" data = [ ['2020-04-24', 40, 38, 'Flensburg, Stadt'],\n",
" ['2020-04-24', 42, 36, 'Flensburg, Stadt'],\n",
" ['2020-04-24', 44, 34, 'Flensburg, Stadt'],\n",
" ['2020-04-24', 9, 10, 'Bamberg']],\n",
" index = [\n",
" 0,\n",
" 1,\n",
" 2,\n",
" 3])\n",
" medianOfFreeBedsByKreisTableFactory = MedianOfFreeBedsByKreisTableFactory(dataFrame)\n",
" \n",
" # When\n",
" medianOfFreeBedsByKreisTable = medianOfFreeBedsByKreisTableFactory.createMedianOfFreeBedsByKreisTable()\n",
"\n",
" # Then\n",
" assert_frame_equal(\n",
" medianOfFreeBedsByKreisTable,\n",
" TestHelper.createDataFrame(\n",
" columns = ['median_free_beds_in_percent'],\n",
" data = [ [statistics.median([40/(40 + 38) * 100, 42/(42 + 36) * 100, 44/(44 + 34) * 100])],\n",
" [9/(9 + 10) * 100]],\n",
" index = pd.Index(\n",
" name = 'Kreis',\n",
" data = [\n",
" 'Flensburg, Stadt',\n",
" 'Bamberg'\n",
" ])),\n",
" check_dtype = False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "af22cdc5",
"metadata": {},
"outputs": [],
"source": [
"unittest.main(argv = [''], verbosity = 2, exit = False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f10704f3",
"metadata": {},
"outputs": [],
"source": [
"medianOfFreeBedsByKreisTableFactory = MedianOfFreeBedsByKreisTableFactory(timeSeries)\n",
"medianOfFreeBedsByKreisTable = medianOfFreeBedsByKreisTableFactory.createMedianOfFreeBedsByKreisTable()\n",
"medianOfFreeBedsByKreisTable.reset_index().to_json('../../docs/data/intensivstationen/medianOfFreeBedsByKreisTable.json', orient = \"records\")"
]
},
{
"cell_type": "code",
"execution_count": null,