updating conda env
This commit is contained in:
@@ -12,4 +12,5 @@ dependencies:
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- lxml
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- lxml
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- jupyter
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- jupyter
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- tensorflow
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- tensorflow
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- nb_conda_kernels
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prefix: /home/frankknoll/anaconda3/envs/howbadismybatch-venv
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prefix: /home/frankknoll/anaconda3/envs/howbadismybatch-venv
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25
src/help.txt
25
src/help.txt
@@ -1,15 +1,5 @@
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jupyter notebook
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jupyter notebook
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zwei Spalten darstellen:
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- linke und rechte Spalte jeweils mit Bundesland-Menu und Landkreise-Submenu des ausgewählten Bundeslandes
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- Dargestellt werden in einem Chart die freien Betten + belegten Betten des ausgewählten Landkreises
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(analog zu "Gesamtzahl gemeldeter Intensivbetten (Betreibbare Betten und Notfallreserve)", siehe https://www.intensivregister.de/#/aktuelle-lage/zeitreihen)
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- Zugrundegelegter Datensatz: zeitreihe-tagesdaten.csv aus https://www.intensivregister.de/#/aktuelle-lage/downloads
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src/intensivstationen/AGS_2022-02-28.json downloaded from https://www.xrepository.de/details/urn:de:bund:destatis:bevoelkerungsstatistik:schluessel:ags
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04-kreise.xlsx: https://www.destatis.de/DE/Themen/Laender-Regionen/Regionales/Gemeindeverzeichnis/Administrativ/04-kreise.html
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COVID-19_Todesfaelle.xlsx: https://www.rki.de/DE/Content/InfAZ/N/Neuartiges_Coronavirus/Projekte_RKI/COVID-19_Todesfaelle.html
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get VAERS data:
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get VAERS data:
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- download data (e.g. 2022VAERSData.zip) from https://vaers.hhs.gov/data/datasets.html and save and unzip in VAERS folder
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- download data (e.g. 2022VAERSData.zip) from https://vaers.hhs.gov/data/datasets.html and save and unzip in VAERS folder
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@@ -17,24 +7,13 @@ get VAERS data:
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FK-FIXME:
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FK-FIXME:
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FK-TODO:
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FK-TODO:
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- Darstellung als Dashboard, siehe https://covid-karte.de/ oder https://experience.arcgis.com/experience/3a132983ad3c4ab8a28704e9addefaba, https://preview.tabler.io/
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- Alle Charts mit Slidern versehen?
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anacron job:
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anacron job:
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sudo cp src/intensivstationen_howbadismybatch.sh /etc/cron.daily/intensivstationen_howbadismybatch
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sudo cp src/intensivstationen_howbadismybatch.sh /etc/cron.daily/intensivstationen_howbadismybatch
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man 5 fcrontab
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fcrontab -e
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fcrontab -l
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# each day at 13:30 Uhr
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30 13 * * * /home/frankknoll/Dokumente/Corona/projects/HowBadIsMyBatch-pages/src/intensivstationen/intensivstationen.sh
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systemctl status fcron
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tail -f /var/log/syslog
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conda create --name howbadismybatch-venv python=3
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conda create --name howbadismybatch-venv python=3
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conda activate howbadismybatch-venv
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conda activate howbadismybatch-venv
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ipython kernel install --user --name=howbadismybatch-venv-kernel
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jupyter kernelspec list
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conda env export --from-history > environment.yml
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conda env export --from-history > environment.yml
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conda env create -f environment.yml
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conda env create -f environment.yml
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@@ -8,7 +8,7 @@ jupyter nbconvert --to html Intensivstationen.nbconvert.ipynb
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mailx -a 'Content-Type: text/html' -s "Intensivstationen" -r Knoll_Frank@web.de Knoll_Frank@web.de < Intensivstationen.nbconvert.html
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mailx -a 'Content-Type: text/html' -s "Intensivstationen" -r Knoll_Frank@web.de Knoll_Frank@web.de < Intensivstationen.nbconvert.html
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cd /home/frankknoll/Dokumente/Corona/projects/HowBadIsMyBatch-pages/src
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cd /home/frankknoll/Dokumente/Corona/projects/HowBadIsMyBatch-pages/src
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conda activate howbadismybatch-venv; jupyter nbconvert --to notebook --allow-errors --execute HowBadIsMyBatch.ipynb
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jupyter nbconvert --ExecutePreprocessor.kernel_name="howbadismybatch-venv-kernel" --to notebook --allow-errors --execute HowBadIsMyBatch.ipynb
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jupyter nbconvert --to html HowBadIsMyBatch.nbconvert.ipynb
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jupyter nbconvert --to html HowBadIsMyBatch.nbconvert.ipynb
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mailx -a 'Content-Type: text/html' -s "How Bad is My Batch" -r Knoll_Frank@web.de Knoll_Frank@web.de < HowBadIsMyBatch.nbconvert.html
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mailx -a 'Content-Type: text/html' -s "How Bad is My Batch" -r Knoll_Frank@web.de Knoll_Frank@web.de < HowBadIsMyBatch.nbconvert.html
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EOF
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EOF
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