ggplot multipanel figure different legend different sizes

#Ggplot multipanel figure different legend different sizes code

The left_join() function retains all the rows in sdcountyand joins any matching rows from the new tablesdclimate`. This column is called “FIPS” in sdcounty and “fips” (lowercase) in sdclimate.

#Ggplot multipanel figure different legend different sizes code

Both sdcounty and sdclimate have a column that contains a unique code for each county and can be used to join the tables. The sdclimate data frame does not contain a geometry columns, so to map precipitaton it will need to be jointed to sdcounty. The columns p3001- p3012 contain the 30-year mean precipitation totals for each month (1-12) and will be used to generate precipitation maps later in the chapter. Next, we important a CSV file that contains climate variables for each county into new a new data frame called sdclimate. Don’t try to modify this column directly - use the functions in the sf package for geospatial data processing. This is a special column that contains the geographic data characterizing each feature (either a point, line, or polygon). The sf object contains a column called geometry. # Mode :character Mode :character Mode :character Median :0.0 # Class :character Class :character Class :character 1st Qu.:0.0

Summary(sdcounty) # STATE COUNTY FIPS C2002 10.3 Summarizing land cover within point buffers.10.2 Summarizing land cover within stream buffers.10.1 Zonal summaries of discrete raster data.10 Combining Raster and Vector Data 2 - Land Cover Data.9.2 Zone size and raster spatial resolution.9 Combining Raster and Vector Data 1 - Gridded Meteorological Data.8.3 Specifying Coordinate Reference Systems.7.6 Mapping specific types of land cover change.7.1 Importing and mapping classified satellite imagery.6.3 Combining Rasters into Bricks and Stacks.

4.2 Modifying the appearance of the map.