LibGuides: R: Mapping and Geospatial: Visualizing

Cartogram

Barry Kronenfeld, Wikimedia Commons

Visualizing / Mapping Packages

See the Getting Data tab of this guide for information on the shift_geometry() function of the tigris Package and the shift_geo = TRUE argument of the tidycensus Package. These create maps of the United States with Alaska, Hawaii, and Puerto Rico shifted (and alternatively rescaled) to closer proximity to the continental US, for more compact visualizations.

sf
The tidyverse package to manipulate and visualize vector data using the Simple Features data structure.
sp
The pre-tidyverse package to manipulate and visualize spatial data.
ggplot2
Create elegant data visualizations compatible with the tidyverse packages using Leland Wilkinson's "Grammar of Graphics."

Try the ggplot2 function stat_density_2d() to create heatmaps indicating density of a point layer. See also the discussion at earthdatascience.org.

ggmap
Spatial visualization using ggplot2: A collection of functions to visualize spatial data and models on top of static maps from various online sources (e.g Google Maps and Stamen Maps). It includes tools common to those tasks, including functions for geolocation and routing.
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Get Census API key to geocode up to 1000 addresses using the geocode() function.
tmap
Thematic maps are geographical maps in which spatial data distributions are visualized. This package offers a flexible, layer-based, and easy to use approach to create thematic maps, such as choropleths and bubble maps.
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Use the qtm() function to draw a thematic map quickly (sort of a preview).
mapview
Create interactive visualisations of spatial data with or without background maps. Attributes of displayed features are fully queryable via pop-up windows. Additional functionality includes methods to visualize true and false-color raster images, bounding boxes, small multiples and 3D raster data cubes.
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Use the mapshot() function to save a mapview or leaflet map as .html index file or .png, .pdf, or .jpeg image.
cartogram
Cartograms distort the shapes of features based on attribute values. Construct continuous and non-contiguous area cartograms
viridis
Implements the viridis and other color maps from Python's matplotlib plotting library. These color maps are designed in such a way that they will analytically be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white.
cividis
This colormap is generated by optimizing the "viridis" colormap and is optimal for viewing by those with or without color vision deficiency (CVD).

Install cividis using devtools. (Install the devtool package if needed.)

# install.packages("devtools")
devtools::install_github("marcosci/cividis")

R: Mapping and Geospatial

Cartogram

Visualizing / Mapping Packages

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