Open christophsax opened 3 years ago
This R package contains data cubes published by the statistical office of Canton Ticino (Ustat). All the data cubes are data.tables in long format, with only one numerical column. These results can also be downloaded in 3 formats (csv, xlsx, px) from the Ustat website.
Used by: Statistical office of Canton Ticino (Ustat)
Shiny app to extract and reshape information from data cubes (from the Ustat site but with other data too). The package also contains shiny modules that could be used to create other shiny apps.
Used by: Statistical office of Canton Ticino (Ustat)
kofdata: Get Data from the 'KOF Datenservice' API
Read Swiss time series data from the 'KOF Datenservice' API, https://datenservice.kof.ethz.ch. The API provides macro economic time series data mostly about Switzerland. The package itself is a set of wrappers around the 'KOF Datenservice' API. The 'kofdata' package is able to consume public information as well as data that requires an API token.
Used by: KOF Swiss Economic Institute, SNB, several cantonal statistical offices
FWIW: will add packages timeseriesdb and tstools after their respective maintenance releases.
staagBevproj
This package projects the population of canton Aargau at cantonal or regional level based on the demographic model of the Swiss Federal Statistical Office (FSO) released in May 2020.
Used by: Statistik Aargau (internal application).
How to access: This package is not available in a public repository. Send us an email.
staaggemeindeport
This package contains the entire collection of code for the shiny app Gemeindeporträt Kanton Aargau which is published here: https://www.ag.ch/app/statistik_aargau_gemeindeportraet/. The app is based on public data published by Statistik Aargau (accessible via different APIs or the official website).
Used by: Statistik Aargau (internal application).
How to access: The package / Code has not been published online yet. Send us an email.
This is the first out of three packages that were created to analyze the BFS "Mikrozensus Mobilität und Verkehr (MZMV) 2015" data. The analysis functions that are included in the MCMTdataanalysis package need a specific data input argument. Since the MZMV data can not be shared freely we created a function that will automatically create this data argument given a path to a folder that contains the original BFS data. This package is intended to be used as the first step to analyze the MZMV thanks to the MCMTdataanalysis package functions.
Used by: Statistical office of Canton Ticino (Ustat)
The aim of this package is to provide a set of tools to select, clean and prepare the "Mikrozensus Mobilität und Verkehr (MZMV)" raw data, to be then analyzed with the MCMTdataanalysis package functions. The MCMTdataprep functions will make use of the data object previously created with the MCMTdatalistcreation package. It will import the data, and select, clean and recode the variables needed to produce the BFS A2 table. This package is intended to be used as the second step to analyze the MZMV data. The MZMV data must be first passed through these functions to be analyzed thanks to the MCMTdataanalysis package.
Used by: Statistical office of Canton Ticino (Ustat)
This package was created with the purpose to analyze the "Mikrozensus Mobilität und Verkehr (MZMV)" based on the BFS methodology. These functions allow any user to reproduce the results as presented in the BFS table A2. The package makes use of the the distrr package, to build data cubes, and therefore to produce results in addition to those in the BFS table. This package is meant to be used after having processed the raw data with the MCMTdatalistcreation and MCMTdataprep packages. This package will be furthermore deveolped to add new features.
Used by: Statistical office of Canton Ticino (Ustat)
rpango
The goal of rpango is to allow access the SARS-CoV-2 pango nomenclature as a tree object in R. This simplifies the manipulation of linelisting containing SARS-CoV-2 information (data validation, grouping to cluster, etc).
This package was developped by the Data Science Team of the Covid-19 Taskforce of the Swiss Federal Office of Public Health with initial contributions from the Computational Evolution group of the D-BSSE of the ETH Zürich. It relies on the Tidyverse ecoystem and the tidygraph package.
This package is not available in a public repository. Send us an email to request access.
This R package specifically focuses on providing an efficient way for creating interactive heatmaps for categorical data or continuous data that can be grouped into categories.
Used by: Stadt Zürich - Verkehrsbetriebe (VBZ) and others
@christophbaur added a new section here: https://github.com/swiss-adminR/pkgs/blob/main/README.md#catmaply-interactive-heatmaps
If you have created an R package that may be useful to other public institutions in Switzerland, please comment on this issue below. We try to to integrate it in the curated list of R packages described here.