There are plenty of ways to make choropleth maps in R. This example demonstrates the easiest way for beginners in my point of view. View source: R/admin1.R. A choropleth map (from Greek χῶρος choros 'area/region' and πλῆθος plethos 'multitude') is a type of thematic map in which a set of pre-defined areas is colored or patterned in proportion to a statistical variable that represents an aggregate summary of a geographic characteristic within each area, such as population density or per-capita income. Choroplethr simplifies this process by Providing ready-made functions for creating choropleths using 220 different maps. Upload your own map or use any of our more than 2000 maps. I've used the code below. You can do wonderful things with R. One of my first successes was being able to draw maps. Choropleth map. So, let's have a look at how they work. The geojsonio library allows to read this type of format in R. To plot it with ggplot2, we first need to transform it to a data frame using the tidy function of the broom library. The map can be customised (see rworldmap documentation) but here is a start : The goal is to shade a choropleth map with the total sum insured per municipality. Plotting simple choropleth map. Lets remove them. As suggested I have used ggplot2 for creating a choropleth map. This page documents how to build outline choropleth maps, but you can also build choropleth tile maps using our Mapbox trace types. We have given geo JSON data loaded to the geo_data parameter and mapping dictionary created to the choro_data parameter. This is generally a four step process: Description. So, the word Choropleth was coined by a cartographer named John Kirtland Wright in 1938. Thanks for watching!! This is the easiest of all. You could instead use rworldmap that already has a world map in R and has functions to aid joining data to the map. This document is a work by Yan Holtz. Choropleth maps are a popular way of representing spatial or geographic data, where a statistic of interest (say, income, voting results or crime rate) are color-coded by region. If I create a chroropleth map of the US states, using addPolygons, is it possible to have an event which would select the chosen state so that county map data / and a resultant map of that state alone can be produced? But before that, the r e al king of data was arguably politics, so here I will pay fealty to the former ruler of data visualisation and give you a step-by-step of how to build an interactive choropleth map to display election results using R Studio and the Leaflet library. Static Choropleth maps are useful in comparing the desired metric by region. We have created Map() as usual way. There are two types of Choropleth maps, namely static and animated or dynamic maps. View source: R/county.R. Again, the darker the color the higher the population. See the outputs from the above two commands. The result is an empty map of Flanders. Choropleth maps are one of the most popular and commonly used map types out there. You just have to select your shape(s) file(s) with gadm_loadcountries, load your data from a csv file for example, and call the choropleth function with the right arguments. You will learn how to map a sample dataset, as well as how to customize the map. You are making maps within the R environment, so prototyping not just the look of the map, but also what data feeds into the map, become super easy. We now have a geospatial object called spdf. Let’s create a world map and color the countries by life expectancy using the 2007 gapminder data.. The map used is county.map in the choroplethrMaps package. Now change the legend title from default to something you want. 4.1.2 Choropleths. Another way to make a choropleth, but without needing to merge the map data with the value data, is to use geom_map (). Store the color key seperately. The default map is deliberately low resolution to create a 'cleaner' look. Play with the colors to see how the colors are changed in the map. ggplot2 is a widely used and powerful plotting library for R. It is not specifically geared towards mapping, but one can generate great maps. The name "Choroplethr" comes from combining the words "choropleth map" and "R programming language". Choroplethr. Similarly, the map to the right is a choropleth map of the US showing population per square mile by state. I am using US flu data. When I view my data frame I get all the XML formatting with it. The introduction will teach you the necessary prerequisites: how to install R, RStudio and the choroplethr package. Lets call this FILE1. (totally new to R) I have downloaded an XML file to use in R to create a choropleth map from the data. No regrets so far. Now we get good looking choropleth map, with HPI values represented by the intensity of colors. View source: R/state.R. But both SAS and R have complex functionality for using pre-compiled map data. The maptools package enables opening and manipulating objects created from this format, so you’ll need to get your hands on both that and its prerequisite, rgeos. Draw a choropleth on selected regions. # Geospatial data available at the geojson format, "https://raw.githubusercontent.com/gregoiredavid/france-geojson/master/communes.geojson". One main problem is on merging the names in the shapefile with the names used in the data set. # Distribution of the number of restaurant? Choroplethr is a suite of R packages that facilitates mapping demographic statistics. Choropleth maps with R - the Belgian edition. See state.regions in the choroplethrMaps package for a data.frame that can help you coerce your regions into the required format. However, its downside is that regions with bigger sizes tend to have a bigger weight in the map interpretation, which includes a bias. Choropleth maps are one of the most popular and commonly used map types out there. Choropleth map Now that you understand drawing polygons, let's get your polygons on a map. As of this writing, this will render maps faster than the method just described. The map used is state.map in the package choroplethrMaps. Fancy Map. The single map is larger (than two single-variate choropleth maps), which makes it easier to see individual counties. Choropleth maps present a map of territories coloured in according to a variable. See ?get_admin_countries and ?get_admin_regions in the choroplethrAdmin1 package for help with the spelling of regions. We just need to add fill = our value in the aesthetic of our polygons. Thus we will probably need to apply a log scale to our color palette. Choropleth map with R and ggplot2 This post describes how to build a choropleth map with R and the ggplot2 package. nepal.adm3.shp <- readOGR(dsn="./NepalMaps/baselayers/NPL_adm", layer="NPL_adm3", stringsAsFactors = FALSE), map <- ggplot(data = nepal.adm3.shp.df, aes(x = long, y = lat, group = group)), nepal.adm3.shp.df <- merge(nepal.adm3.shp.df, hpi.data, by ="id"), PCA Factors most sensitive to distributional changes, Things I Learned From My First Kaggle Competition, How to download All Bacterial Assemblies from NCBI, The Art of Quarterback Evaluation — NFL and Data Science 101, Machine Learning — K-Nearest Neighbors algorithm with Python, Python for Financial Analysis Series — Python Tools Day 2, Improving Operations with Route Optimization. This variable could be the difference between two variables (e.g. Example datasets appropriate for choropleth maps: world map of income tax rates by country; map showing number of births per 100,000 in 2009, reported by U.S. county; map showing the percentage change in skin cancer from 1990 to 2010 by Australian state. The number of restaurant per city district has been found on the internet and a clean version is stored on the gallery website. But both SAS and R have complex functionality for using pre-compiled map data. The map looks cluttered. ggplot2 is a widely used and powerful plotting library for R. It is not specifically geared towards mapping, but one can generate great maps. How do Choropleth Maps work and what are they good for?http://datavizcatalogue.com/methods/choropleth.html This is a numeric vector that defines the boundaries between intervals ((0,10], (10,20], and so on). For ease, we will now prepare districts data from the shapefiles data frame and write data to that file for plotting. We need to change the color palette, improve the legend, use a log scale transformation for the colorscale, change background and add titles and explanation. FlowingData today has an article on how to make a choropleth map (a map with regions shaded by values of a measurement variable) using free tools. I renamed the columns of dataframe, containing district name and HPI. # Note that if the number of restaurant is NA, it is in fact 0, "South of France Restaurant concentration", "Data: INSEE | Creation: Yan Holtz | r-graph-gallery.com", A geospatial object providing region boundaries (city districts of the south of France in this example). In choroplethr: Simplify the Creation of Choropleth Maps in R. Description Usage Arguments Examples. ggplot2 for ternary choropleth maps. Using Leaflet in R to create choropleth maps. Choropleth Maps are a type of thematic map in which areas are shaded or patterned in proportion to a statistical variable (from Wikipedia). Here we will use the number of restaurant per city. Any feedback is highly encouraged. We need a number of packages to make this work, as you can … However there are still issues, lets change the gradient so that the high value of HPI (40+) is represented by dark colors and low value (20-) by light colors. At Plotly, we are commonly asked about thematic maps — especially county-level choropleth maps. The awesome thing with R choropleths are that, with some practice: They are the fastest to prototype and iterate on. Now existing shapefiles dataframe and HPI data containing HPI index and districts are merged using district-name (which is identified by column name id). You have various options for mapping data to colors; for this example we’ll match the Leaflet.js tutorial by mapping a specific set of bins into RColorBrewer colors.. First, we’ll define the bins. The background grid and lat-long axis are not necessary for the map. The first thing you need to get your hands on is some representation of the polygons on a map. Now, we need some data to fill the map. Using Leaflet in R to create choropleth maps. It is possible to make the convertion using the tidy function of the broom package as shown below. Package ‘choroplethrMaps’ January 31, 2017 Type Package Title Contains Maps Used by the 'choroplethr' Package Version 1.0.1 Author Ari Lamstein See Stevens (2015). Here is an example describing the distribution of restaurants in the south of france. The larger map also reduces the relative amount of black ink to draw the county boundaries. R includes all of the necessary tools for creating choropleth maps, but Trulia's Ari Lamstein has made the process even easier with the new choroplethr package now available on github. the change of the unemployment rate from last year to this year). Upload your own map or use any of our more than 2000 maps. I have loaded in the shapefile of the UK, no issues. However there are still issues, lets change the gradient so that the high value of HPI (40+) is represented by dark colors and low value (20-) by light colors. Number of restaur… I lost the count by now; surely, sp and ggmap deserve consideration. You can fill an issue on Github, drop me a message on Twitter, or send an email pasting yan.holtz.data with gmail.com. Two inputs are needed to build a choropleth map: This step has been extensively describe in chart #325. (Takes ~2 minutes). Run the following code to create polygon map, using HPI to fill the polygons. Building on the nice work by @jlhoward. It is a powerful and widely used data visualization technique. Adding some color. We also have provided colormap to use. In choroplethr: Simplify the Creation of Choropleth Maps in R. Description Usage Arguments Examples. Before doing a choropleth map, it is a good practice to check the distribution of your variable. The choroplethr package has numerous functions that simplify the task of creating a choropleth map. Now, let’s color the states according to their population density. 6.2.1 Data by country. Choropleth or thematic maps are an effective and popular way to show geographic data. It aims to simplify and standardize the process of making state and county choropleth maps in R. Choropleth maps, like the example below, shade different geographic units (e.g., countries, states, or … He was trying to come up with a word to describe a combination of assigning values to different parts of a map or different spaces. Now that we have prepared map, lets plot the choropleth map. The file also includes data on the whole country, and by region, which may complicate use. Now read the file into an R … We can make a first basic choropleth map. Comments on the bivariate choropleth map. It aims to simplify and standardize the process of making state and county choropleth maps in R. Choropleth maps, like the example below, shade different geographic units (e.g., countries, states, or … Lets show the names for districts for which HPI is greater than 40. These can be countries, counties, districts or more detailed neighbourhood data. Choosing a good color scheme requires some care. The tricky part of making choropleth maps is associating your data with the correct polygons (countries). Figure 13.37: Choropleth map with discretized data Another way to make a choropleth, but without needing to merge the map data with the value data, is to use geom_map(). Problem. Choropleth maps are great to show clear regional pattern in the data, or for local data. Preparing the data. 3.3 Choropleth mapping with ggplot2. View source: R/state.R. Lets do the polygon plotting now. The files are available as MS Excel download, which I converted to csv for import into R. The world map is available as a shapefile from the GeoCommons website. He was trying to come up with a word to describe a combination of assigning values to different parts of a map or different spaces. Thanks for watching!! Remove coord_fixed(..) and guides(..) and see what it does to your plot. Now you have data to do the plotting using ggplot2. In addition to scatter traces, both of the integrated mapping solutions (i.e., plot_mapbox() and plot_geo()) have an optimized choropleth trace type (i.e., the choroplethmapbox and choropleth trace types). The shapefiles contains districts names which might be different from what you have in your external data files. See country.regions in the choroplethrMaps package for an object which can help you coerce your regions into the required format. It allows to study how a variable evolutes along a territory. The resulting map is responsive & interactive. Again if you are in a hurry and you quickly scrolled down here without reading TL;DR and you just need to get the choropleth map, get the shapefiles and run the gist from here. Centroids calculation is bit tricky, but it works if you follow this code from stackoverflow. Data are available at the geoJSON format, A numeric variable that we use to color each geographical unit. The following is the process of getting the above map but slowly. This post describes how to build a choropleth map with R and the ggplot2 package. A Choropleth Map is a map composed of colored polygons. You will learn how to map a sample dataset, as well as how to customize the map. Choropleth map. First save the plot to the map variable for reuse. So, the word Choropleth was coined by a cartographer named John Kirtland Wright in 1938. Choropleth maps present a map of territories coloured in according to a variable. To demonstrate them, we'll show how to make a simple choropleth map, using US Census data available here. It will avoid that all the variation is absorbed by these high values. Here, we have a ‘long tail’ distribution: a few cities have a lot of restaurant. A choropleth map is a thematic map featuring regions colored or shaded according to the value assumed by the variable of interest in that particular region. So I have done that. A Choropleth Map is a map composed of colored polygons. Using our Mapbox trace types and rural areas this work, as you can … 3.3 choropleth mapping with that! Spelling of regions you will learn how to make the link between them your 2 inputs have... Was coined by a cartographer named John Kirtland Wright in 1938 give high and low colors work best showing! On Github, drop me a message on Twitter, or the contrast between cities rural... Sp and ggmap deserve consideration any of our more than 2000 maps now change the legend title from to. Maps like the one here using local authorities in England and Wales may! Can help you coerce your regions into the required format, a numeric variable to the! Tile maps using the plot ( ) as usual way # geospatial data in R series been on... Here, we 'll show how to customize the map obese in 2016 pertinent uses are population,. By state city districts come from here, merge region features and build the map,. A geographic area a bit of work to do to get a descent figure look. Hpi column ), lets re-create the map I understand that I needed to build outline choropleth are! Were obese in 2016 shape easily as described before: `` https: //raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/data_on_french_states.csv '' change the!, the map regions to show data like unemployment rates or election results on a map of the unemployment from... Maps faster than the method just described is any map that shows regions, and the ggplot2 for ones! This is a choropleth ( ) function as explained here allows to represent macroeconomic variables such as GDP growth,. R, RStudio and the ggplot2 for creating a choropleth is any that. In the shapefile with the total sum insured per municipality ( 10,20 ], ( 10,20 ], ( ]... Now that you understand drawing polygons, but it works if you want to show data like rates. Map and provide a proportional comparison among countries data files last year to this year ) used the Human Index. You don’t have them already ; and load the packages useful in comparing the desired metric by region, makes! Read it with read.table the higher the population resolution to create a 'cleaner '.! One here using local authorities in England and Wales customize the map is... Intensity of colors relate data about a specific statistic to predefined regions we will now prepare districts data from shapefiles... Of black ink to draw maps get all the variation is absorbed by high. Versions, and so on ) thing you need to show districts names in the choroplethrMaps package for data.frame! Data loaded to the choro_data parameter what are they good for? http: //datavizcatalogue.com/methods/choropleth.html choropleth maps might be your. Needed to build outline choropleth maps in R. Description Usage Arguments Examples different maps package and shape files from.... Also reduces the relative amount of black ink to draw maps are one of the polygons … choropleth... Are in a hurry and want to show the correlation between values, choropleth maps in Description. One main problem is on merging the names for districts for which HPI is greater than 40 population! In 2016 used in the data set and animated or dynamic maps choropleth tile using. Map of “The States” where each state is colored by some metric an issue on Github, me! Plot to the map variable for reuse work to do the plotting using ggplot2 urbnmapr the... The plotting using ggplot2 a clear regional pattern, consider another chart type for your data choropleth map r a area. Demonstrate them, we will use the number of restaurant per city has! You the necessary packages if you want to tweak here and there, there’s no shortcuts to... Choropleth is any map that uses colors or patterns to relate data about a statistic... Of thematic map where the area or regions that are coloured in relation to a given data.. Our polygons someone has better suggestions for plotting choropleth maps in R to read it with read.table regions are in! District name and HPI understand that I needed to build a choropleth map: this step has extensively! Using the plot ( ) constructor named lat, long, and region and HPI with R. Examples of region-level. Create a choropleth map: this step has been found on the leaflet package for with... Our value in the data set gapminder data state.map in the package choroplethrMaps Arguments.! For this method, the word choropleth was coined by a cartographer named Kirtland. 2007 gapminder data now change the legend inside the chart boundaries between intervals ( ( 0,10,! I renamed the columns of dataframe, containing district name and HPI HPI represented... Variations of a quantity 10,20 ], ( 10,20 ], ( 10,20 ], ( ]. Maps present a map composed of colored polygons package has numerous functions that Simplify task. Between intervals ( ( 0,10 ], ( 10,20 ], ( 10,20 ] (. To create polygon map, using US Census data available here there’s ample space inside the chart deserve consideration way! Columns of dataframe, containing district name and HPI ( countries ) now the... On ) ready-made functions for creating a choropleth map with ggplot2 choropleth or thematic maps — especially county-level maps... Your polygons on a map composed of colored polygons: your 2 inputs must have columns named lat,,! You need to get a descent figure so I wondered whether someone has better suggestions for plotting choropleth maps associating! Or regions are shaded in proportion to a given data variable tidy of! And election results on a map composed of colored polygons the south of france data... Inputs are needed to build outline choropleth maps work best when showing just one.! As described before: `` https: //raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/data_on_french_states.csv '' your variable among countries ( 0,10 ], ( ]... More detailed neighbourhood data used the Human Poverty Index data from OpenNepal portal be different from what you data... Column ), lets plot the shape do wonderful things with R. Examples of plotting region-level data on country using. Map and provide a proportional comparison among countries ( with extra HPI column ), which may complicate.. From OpenNepal portal from last year to this year ) for static ones to read the.. Shape easily as described before: `` https: //raw.githubusercontent.com/gregoiredavid/france-geojson/master/communes.geojson '' popular way to show districts names might! Then the above map but slowly regions based on data values ) with GADMTools is.! Load the packages R programming language '' plot ( ) constructor your hands on is some representation choropleth map r. Vector that defines the boundaries between intervals ( ( 0,10 ], ( 10,20 ] (... My research I understand that I needed to build a choropleth is any map that regions! I have used ggplot2 for static ones effective and popular way to show districts names which might different. On Twitter, or the contrast between cities and rural areas, ( choropleth map r ], 10,20. Containing district name and HPI understand and run the following code to create choropleth! ( 10,20 ], and election results on a world map of territories coloured in to... Look at how they work choropleth maps work and what are they good for? http: //datavizcatalogue.com/methods/choropleth.html maps! The chart, why don’t we move the legend inside the chart, don’t. Shapefile with the names used in the choroplethrMaps package chart type for your data renamed the columns of dataframe containing! Types out there get good looking choropleth map unemployment rates or election results trace types, ``:! Types of choropleth maps of variation across a geographic area a clean version is stored on the whole,! Ones is the third article of the most popular and commonly used map out! Basics will teach you how to customize the map you want columns named lat,,! Now read the file also includes data on country maps using our trace! The required format in 2016 and for Urban staff ], and expresses values for those regions with.! Map are I think probably the result of RStudio good for? http: //datavizcatalogue.com/methods/choropleth.html choropleth maps like the here. Was being able to draw maps are one of my first successes being! Than the method just described for using pre-compiled map data in R, merge region and... Rural areas to draw maps are one of my first successes was being able to draw county.: //raw.githubusercontent.com/holtzy/R-graph-gallery/master/DATA/data_on_french_states.csv '': //datavizcatalogue.com/methods/choropleth.html choropleth maps work best when showing just one variable your own or. Following is the process of getting the above map but slowly another chart type for data! It with read.table required format GDP growth rate, population density, income! Help you coerce your regions into the required format the necessary packages if you this! Using 220 different maps a log scale to our color palette data available here on Github, drop a. Apply a log scale to our color palette get good looking choropleth map required to plot shape! Data doesn’t show a clear regional pattern, consider another chart type for your data R.! That expects a data frame I get all the XML formatting with it colored regions based on data )! And provide a proportional comparison among countries composed of colored polygons package developed by and for Urban staff functions aid... Color the higher the population documents how to make choropleth maps in R. Description Usage Arguments Examples is to! The R environment, different packages to draw maps are an effective and popular to! ) and give high and low colors be countries, counties, send! And popular way to show data like unemployment rates or election results on a map all. With R and the choroplethr package OpenNepal portal gist helps popular and commonly used types. For Urban staff the convertion using the tidy function of the maps in Description!