Working with Shapefiles in R Exercises
R has many powerful libraries to handle spatial data, and the things that R can do with maps can only grow. This exercise tries to demonstrate a few basic functionalities of R while dealing with shapefiles.
A shapefile is a simple, nontopological format for storing the geometric location and attribute information of geographic features. Geographic features in a shapefile can be represented by points, lines, or polygons (ESRI). The geographic features are associated with an attribute table which is very similar to an R dataframe.
rgdal package in R provides bindings to the popular Geospatial Data Abstraction Library (GDAL) for reading, writing and converting between spatial formats. We are using a very popular dataset of London sports participation shapefile (download here). The attributes
Partic_Per represents the population of London Boroughs in 2001 and the percentage of the population participating in sporting activities.
Answers to the exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page.
Please install and load the package
rgdal before starting the exercises.
Read the London Sports map from the shapefile
Change the coordinate system of the map to WGS 84.
Find the names of the zones where sports participation rates is more than 25%.
Plot the london map in Sky Blue, along with a title.
Plot the zones in London with Sports Participation Rates less than 15% in red. Retain the earlier blue color for other zones.
Plot the zones in London with Sports Participation Rates more than 25% in green. Retain the earlier color for other zones.
Place a black circle marker at the centre of each zone. Retain previous maps.
Put labels for each zone. Place the labels to the right of the black marker.
Add another categorical attribute
sports_part which has values
"low", "medium" and "high" for sports participation rates less than equal to 15%, between 15 to 25% and greater than 25% respectively.
Save the new map object with modified attribute table as a new shapefile “london_sport2.shp”.