mapping.R

# Load the library
library(ggplot2)
library(ggmap)

# Create a dummy data frame of points
set.seed(500)
df <- round(data.frame(
  lon = jitter(rep( 77.59, 50), amount = .3),
  lat = jitter(rep( 12.97, 50), amount = .3)
), digits = 2)

View(df)

# Just plotting the points 
ggplot(df) + aes(lon, lat) + geom_point()

# Plotting with coordinate system for map
ggplot(df) + aes(lon, lat) + geom_point() + coord_map("mercator")

# Get lat and lon for a place
geocode("Bangalore")

# Get a map
map <- get_map("Bangalore")
ggmap(map)

# You can get other maps - Open Street Map, Stamen etc.
map1 <- get_map("Bangalore", maptype = "toner", source = "stamen")
ggmap(map1)

# Plot the data
ggmap(map1) + geom_point(data = df, aes(lon, lat), 
                         color = "red", size = 6)


# Plot a Choropleth
library(choroplethr)
library(scales)
str(df_pop_state)                 
View(df_pop_state)
ggplot(df_pop_state) + aes(reorder(region,value), weight = value) +
  geom_bar() +  coord_flip() + scale_y_continuous(labels = comma)

# Get map shapes 
library(maps)
map("state")
states <- map_data("state")

# Combine the data set and create choropleth
choro <- merge(states, df_pop_state, sort = FALSE, by = "region")

ggplot(choro) + aes(long, lat, group = group, fill = value) +
  geom_polygon() + coord_map()