Website to compute usage of tax money by the Swiss government and cantons.
Similar implementation (using old data) available at: https://www.srf.ch/news/schweiz/persoenlicher-steuerrechner-wofuer-zahle-ich-steuern, code at https://srfdata.github.io/2019-02-steuern/.
Inform the public about the usage of tax money in a simple and clear interface. Additionally, we want to learn about the structure of the government and improve our software develoment skills.
The data of the confederation and of cantons is exported from the files data/sources/bund.xlsx and data/sources/ktn_XX.xlsx.
These are part of the archive made available by the federal administration at https://www.efv.admin.ch/efv/en/home/themen/finanzstatistik/daten.html.
The expenses are read from the sheet ord_ausgaben_funk, in which they are grouped by function. This is in order to be able to compare the confederation with individual cantons.
Each function has a unique ID identifying it and the corresponding labels are stored once.
The IDs are further splitted in category and subcategory, each category is a single digit ID between 0 and 9. The subcategories vary in number, but are represented by one subcategory digit between 1 and 9 appended to the category digit. For example the category "Social security" has ID 5, and its subcategory "Subsidized housing" has the ID 56.
The expenses are computed as a share of total expenditure of the Canton/Confederation and stored as a fractional number.
GDP data is exported from data/sources/bip.csv, available at https://www.bfs.admin.ch/bfs/de/home/statistiken/kataloge-datenbanken/tabellen.assetdetail.27065234.html.
| Name | Type | Content |
|---|---|---|
| PERIOD | string | Year |
| VARIABLE | string | "GDP": Gross domestic product "GDPPC": Gross domestic product per capita |
| VALUE | float | Numeric value |
| UNIT_MEAS | string | "MCHF": Million CHF "AC": Annual change with current prices in % "ACPP": Annual change with prices of previous year in % |
The input data is processed with the Pyhton script data/process_data.py.
The processed data is stored in one file per year data/data_YYYY.json.
The labels of the expenses are stored in data/labels.json
The files are structured as in the example file structure.txt.