In arc2r/book: All things R Spatial or A guide to spatial R for Recovering ArcGIS Users

library(arc2r)
library(sf)
library(ggplot2)
library(dplyr)

# Read the dataset depicting the districts (Bezirke) in the country of Switzerland
data("bezirke")

# sort the dataset based on the Area in ascending order
bezirke_asc <- bezirke[order(bezirke$area_km2),]
head(bezirke_asc)

# sort the dataset based on the Area in descending order
bezirke_desc <- bezirke[order(-bezirke$area_km2),] 
head(bezirke_desc)

# sort the dataset based on the Area in ascending order
bezirke_arrange_asc <- arrange(bezirke,area_km2) # by default the function sorts in ascendind order
head(bezirke_arrange_asc)

# sort the dataset based on the Area in descending order
bezirke_arrange_desc <- arrange(bezirke,-area_km2)
head(bezirke_arrange_desc)

# Reading the dataset that depicts all the swimming spots in the canton of Zurich
data("badeplaetze_zh")

# Renaming the dataset above to "swimming_spots_zh"
swimming_spots_zh <- badeplaetze_zh

# Retrieving the address in memory for the two datasets
tracemem(badeplaetze_zh) # --> <000001F24AB616E8>
tracemem(swimming_spots_zh) # --> <000001F24AB616E8>

# Using the dataset that depicts all the 26 Cantons of Switzerland
data("kantonsgebiet")

# Selecting the Canton of Zug
zug <- filter(kantonsgebiet, NAME == "Zug") # depicting the Canton of Zug
ggplot(zug) + geom_sf() # depicting the Canton of Zug

# Selecting the Canton of Zürich
zurich <- filter(kantonsgebiet, NAME == "Zürich")
ggplot(zurich) + geom_sf() # depicting the Canton of Zurich

# merging the two sf objects
merged <- rbind(zug,zurich)
ggplot(merged) + geom_sf() # depicting the product of the merge operation

# The study area from the previous example
head(kantonsgebiet)
ggplot(kantonsgebiet) + geom_sf() # depicting all the 26 Cantons of Switzerland

# Dissolving all the cantons into one unified area
kantonsgebiet_dissolved <- st_union(kantonsgebiet) # use of the sf__st_union() function
head(kantonsgebiet_dissolved)

# Plot the dissolved output
ggplot(kantonsgebiet_dissolved) + geom_sf()

# create the duplicates
addDupli <- kantonsgebiet[1:3,]

# Combine it with the original dataset (kantonsgebiet)
kantonDuplic <- rbind(kantonsgebiet, addDupli)

# Examine if there are any identical values
ident_results <- st_equals(kantonDuplic)

arc2r/book documentation built on March 5, 2021, 2:10 p.m.