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# Covid data visualization and analysis for Slovenia | ||
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This was my personal project for visualizing and analyzing COVID-19 data for Slovenia during the first wave of the pandemic in spring 2020. I started it on 13. march (beginning of the first lockdown), and kept updating and improving it until april, when [Sledilnik](https://covid-19.sledilnik.org/sl/stats ) became good enough to replace most of it. | ||
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Raw data (number of cases and tests) was gathered from various sources, then combined, cleaned and analysed in Python. The visualizations were done in Python inside Jupyter Notebook using `pandas`, `matplotlib` and `seaborn`. Predictions were calculated using [SIR-X model](http://rocs.hu-berlin.de/corona/docs/forecast/model/). At first I was exporting the results as a pdf of the entire notebook, but later switched to exporting just the images. | ||
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Below you can see example visualizations for 1. april. Final analysis for the last day changes were made (4. april 2020) is in the [Korona.ipynb](Korona.ipynb) notebook, and the corresponding images are in the [images](images) folder. Check out the [archive](archive) folder for earlier data. *Note that everything is in Slovenian*. | ||
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### Sources of the data (some may not work anymore): | ||
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1. NIJZ: *[Spremljanje koronavirusa SARS-CoV-2 (COVID-19)](https://www.nijz.si/sl/pojav-novega-koronavirusa-2019-ncov)* | ||
2. NIJZ: *[Dnevno spremljanje okužb s SARS-CoV-2 (COVID-19) [graph]](https://www.nijz.si/sl/dnevno-spremljanje-okuzb-s-sars-cov-2-covid-19)* | ||
3. Data published by the government on *[gov.si](https://www.gov.si/teme/koronavirus/)* and *[twitter](https://twitter.com/vladaRS)*. | ||
4. Luka Renko and others: *[COVID-19 Slovenija](https://slo-covid-19.rtfm.si/#/about)* | ||
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## Graphs for 4. april | ||
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### Cases | ||
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Cumulative & daily new cases (linear and log scale), growth analysis (new cases as percentage of all, doubling time) | ||
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 | ||
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### Tests | ||
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Cumulative & daily new (linear and log scale), daily and overall positive percentage | ||
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 | ||
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### Hospitalized | ||
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Hospitilized patients, ICU patiens and cumulative deaths, both absolute and as a percentage of cumulative infections | ||
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 | ||
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### Cases by age | ||
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Cumulative and daily new cases by age group (total and per 100k population), both absolute and relative | ||
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 | ||
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### Cases by region | ||
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Cumulative and daily new cases by region (total and per 100k population), both absolute and relative | ||
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 | ||
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### Predictions (4. april) | ||
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Predictions for the next week using [SIR-X model](http://rocs.hu-berlin.de/corona/docs/forecast/model/) | ||
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 |
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