Time Series, Maps, Interactive Graphs

• line graphs
• area charts
• stacked area charts
• dumbell and slope graphs (not covered)

Convert character values to dates

example

x <- c("10/2/2008", "12/5/2008")
xDate <- as.Date(x, format="m/d/Y")

see https://www.statmethods.net/input/dates.html

library(ggplot2)
ggplot(data, aes(x = datevar, y = )) +
  geom_line() 

customize x-axis using

+ scale_x_date(date_breaks = , labels =)

ggplot(data, aes(x = datevar, y = )) +
  geom_area(fill=, color=)

Stacked area chart

ggplot(data, aes(x = datevar, y = , fill=)) +
  geom_area(color=)

• ggplot2 graphs are static by nature

• any ggplot2 graph can be made interactive via plotly

Steps

• create ggplot2 graph
• save it as an object
• process it with the ggplotly function

library(ggplot2)
library(plotly)
p <- ggplot(economics, 
            aes(x = date, y = psavert)) +
  geom_line() 
ggplotly(p)

• dot density
• choropleth

Each observation should include longitude and latitude

• interactive maps with leaflet
• select a leaflet provider http://leaflet-extras.github.io/leaflet-providers/preview/index.html

library(leaflet)

leaflet() %>% 
  addProviderTiles(providers$namehere) %>%
  setView(lng = , lat = , zoom = ) %>%
  addCircles(lng =, lat =, popup =, color =)

type providers at the console to see provider names

Easy choropleth maps with the choroplethr package by Ari Lamstein

• country_choropleth()
• state_choropleth()
• county-chorpleth()
• zip_chorpleth()

Resulting maps are ggplot2 graphs and can be further modified.

library(chorplethr)
country_choropleth(data, "title", num_colors = , zoom = )

• data should have two columns (region and value)
• Elements in the “region” column must exactly match how regions are named in the “region” column in ?country.map.
• num_colors - number of colors used in map (0-9) with 0 for divergent scale and 1 for continuous scale.
• zoom is a character vector listing countries

library(chorplethr)
state_choropleth(data, "title", num_colors = , zoom = )

• data should have two columns (region and value)
• Elements in the “region” column must exactly match how regions are named in the “region” column in ?state.map.
• num_colors - number of colors used in map (0-9) with 0 for divergent scale and 1 for continuous scale.
• zoom is a character vector listing states

library(chorplethr)
county_choropleth(data, "title", num_colors = , 
                  state_zoom = , county_zoom = )

• data should have two columns (region and value)
• Elements in the “region” column must exactly match how regions are named in the “region” column in ?county.map.
• num_colors - number of colors used in map (0-9) with 0 for divergent scale and 1 for continuous scale.
• state_zoom and county_zoom are state and county vectors

modify choroplethr graph with ggplot2 functions

example

library(chorplethr)
county_choropleth(data, "title", num_colors = , 
                  state_zoom = , county_zoom = ) +
  scale_fill_brewer(palette = "Set1")

see https://r-graph-gallery.com/38-rcolorbrewers-palettes.html