RSwissMaps

Plot and Save Customised Swiss Maps


Keywords
canton, cran-r, districts, ggplot2, map, maps, municipalities, rstats, switzerland, visualisation, visualization
Licenses
CNRI-Python-GPL-Compatible/CNRI-Python-GPL-Compatible

Documentation

CRAN_Status_Badge Build Status Licence cranlogs

RSwissMaps

RSwissMaps allows to link thematic data to Swiss administrative divisions (municipalities, districts, cantons) and to plot it on a map. The maps can be customised (to some degree) and saved in different resolutions and formats. The package also allows to generate tailored templates for data collection. The geodata used is publicly available on the Swiss Federal Statistical Office website.

Data availability

Geodata of Swiss municipalities, districts, and cantons is currently available for the following reference dates: 2001-1-1, 2002-1-1, 2003-1-1, 2004-1-1, 2005-1-1, 2006-1-1, 2007-1-1, 2008-1-1, 2009-1-1, 2010-1-1, 2010-31-12, 2011-1-1, 2011-31-12, 2012-1-1, 2012-31-12, 2013-1-1, 2013-31-12, 2014-1-1, 2014-31-12, 2015-1-1, 2015-31-12, 2016-1-1, 2016-31-12, 2017-1-1.

Coordinate reference system

CH1903/LV03 (EPSG:21781). For more information, please see: swisstopo and Spatial Reference

Commercial use

For commercial use of the data, please see: GEOSTAT, BFS

Installation

Version 0.1.0 is on CRAN, and you can install it by:

install.packages("RSwissMaps")

For regularly updated version (latest: 0.1.4) with all geodata pre-installed, install from GitHub:

install.packages("devtools")
devtools::install_github("zumbov2/RSwissMaps", subdir = "allinone")

Examples

Example 1 (with code)

municipalities

gemeinden <- mun.template(2017)

for(i in 1:nrow(gemeinden)){
  gemeinden$values[i] <- sample(c(300:700), 1)/1000
}

mun.plot(gemeinden$bfs_nr, gemeinden$values, 2017,
         color_continuous = c("#c7e9c0", "#006d2c"),
         boundaries_size = 0.2,
         title = "Random data",
         subtitle = "Schweizer Gemeiden, 2017",
         caption = "Plotted with RSwissMaps",
         save = T,
         dpi = 1000)

Example 2 (with code)

municipalities2

gemeinden <- mun.template(2017, cantons = c("AG", "ZH"))

for(i in 1:nrow(gemeinden)){
  
  gemeinden$values[i] <- sample(c(300:700), 1)/1000
  
}

mun.plot(gemeinden$bfs_nr, gemeinden$values, 2017,
         cantons = c("AG", "ZH"),
         lakes = c("Hallwilersee", "Zürichsee", "Greifensee"),
         boundaries = c("m", "c"), boundaries_color =  c("white", "white"),
         boundaries_size = c(0.2, 1),
         title = "Random data",
         subtitle = "Aargauer und Zürcher Gemeiden, 2017",
         caption = "Plotted with RSwissMaps",
         save = T,
         filename = "mun_plot2.png",
         dpi = 1000)

Example 3 (real data)

districts

Example 4 (real data)

cantons