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https://github.com/sdesabbata/BivariateTMap
A simple function to create bivariate Choropleth maps in R tmap
https://github.com/sdesabbata/BivariateTMap
Last synced: about 2 months ago
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A simple function to create bivariate Choropleth maps in R tmap
- Host: GitHub
- URL: https://github.com/sdesabbata/BivariateTMap
- Owner: sdesabbata
- License: gpl-3.0
- Created: 2018-11-28T14:41:22.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2018-11-29T09:21:00.000Z (almost 6 years ago)
- Last Synced: 2024-05-21T01:14:21.127Z (4 months ago)
- Language: R
- Size: 88.9 KB
- Stars: 23
- Watchers: 5
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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- jimsghstars - sdesabbata/BivariateTMap - A simple function to create bivariate Choropleth maps in R tmap (R)
README
# Bivariate tmap
The *bivariate_tmap.R* script defines a simple function named *bivariate_choropleth* which uses the [*tmap*](https://cran.r-project.org/web/packages/tmap/) library to create a bivariate choropleth map (using a color scheme fro [Joshua Stevens's fantastic blog post](http://www.joshuastevens.net/cartography/make-a-bivariate-choropleth-map/)) and plot it including a legend created using the [grid](https://stat.ethz.ch/R-manual/R-devel/library/grid/html/Grid.html) library.
The *bivariate_choropleth* function parameters are:
* *bivmap_dataset*, a SpatialPoligonDataFrame;
* *bivmap_vars*, a vector of characters containing the name of the two variables;
* *bivmap_labels*, a vector of characters containing the labels for the two variables, to use in the legend (default is *NA*, in; which case, values from *bivmap_vars* are used);
* *bivmap_style*, classification type for the bins (default is *'quantile'*);
* *bivmap_scale*, whether to use a scale bar (default is *FALSE*).
The *bivariate_choropleth* function uses a function named *get_bivariate_choropleth* which simply creates the map (without the legend) and returns the related object. This function can also be used directly for further manipulation of the map.
## Requirements
The function was developed using R version 3.5.1, and it requires the following R libraries:
* [sp](https://cran.r-project.org/web/packages/sp/)
* [spdep](https://cran.r-project.org/web/packages/spdep/)
* [tmap](https://cran.r-project.org/web/packages/tmap/)
* [classInt](https://cran.r-project.org/web/packages/classInt/)
* [grid](https://stat.ethz.ch/R-manual/R-devel/library/grid/html/Grid.html)
* [gridExtra](https://cran.r-project.org/web/packages/gridExtra/)
* [lattice](https://cran.r-project.org/web/packages/lattice/)
## Example
Example script.
```r
# Import function
source("bivariate_tmap.R")
# Import example data
library(tmap)
data("World")
# Transform data to SpatialPolygonDataFrame
library(sf)
world_spdf <- as(World, "Spatial")
# Plot bivariate choroplet map
bivariate_choropleth(world_spdf, c("gdp_cap_est", "inequality"))
```
Console output (categories).
```
gdp_cap_est breaks (x-axis):
style: quantile
[300.4693,3356.704) [3356.704,13587.93) [13587.93,2e+05]
59 58 59
inequality breaks (y-axis):
style: quantile
one of 9,045 possible partitions of this variable into 3 classes
[0.0432207,0.1672642) [0.1672642,0.2736572) [0.2736572,0.5073423]
45 45 46
```
Output map.
## Acknowledments
I would like to acknowledge the contribution by [Andrea Ballatore](https://twitter.com/a_ballatore), who collaborated on the [paper](https://link.springer.com/chapter/10.1007/978-3-319-78208-9_8) for which I originally wrote this script, helped me testing it, and encouraged me to publish it.