Time series visualization with ggplot2 Rstudio (country-level)-CodePudding

I'm just learning R fundamentals, and I would like to ask your help with data visualization, and specifically time series. I'm studying how vote shares of a specific category of political parties (right-wing populists) vary overtime in each country from 2009 to 2019. Here's my dataset:

dput(votesharespop)
structure(list(country = c("Austria", "Belgium", "Bulgaria", 
"Czech Republic", "Denmark", "Estonia", "Finland", "France", 
"Germany", "Great Britain", "Greece", "Hungary", "Italy", "Lithuania", 
"Luxembourg", "Netherlands", "Poland", "Romania", "Portugal", 
"Slovakia", "Slovenia", "Spain", "Sweden", "Austria", "Belgium", 
"Bulgaria", "Czech Republic", "Denmark", "Estonia", "Finland", 
"France", "Germany", "Great Britain", "Greece", "Hungary", "Italy", 
"Lithuania", "Luxembourg", "Netherlands", "Poland", "Romania", 
"Portugal", "Slovakia", "Slovenia", "Spain", "Sweden", "Austria", 
"Belgium", "Bulgaria", "Czech Republic", "Denmark", "Estonia", 
"Finland", "France", "Germany", "Great Britain", "Greece", "Hungary", 
"Italy", "Lithuania", "Luxembourg", "Netherlands", "Poland", 
"Romania", "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden"
), year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 
2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 
2009, 2009, 2009, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 
2014, 2014, 2014, 2014, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
2019, 2019, 2019, 2019, 2019), vote_share = c(17.3, 15.7, 16.7, 
4.3, 15.3, 0, 9.8, 8.1, 1.7, 22.7, 7.2, 71.2, 45.5, 12.2, 7.4, 
17, 27.4, 8.7, 0, 5.6, 35.2, 0, 3.3, 20.2, 7.6, 16.8, 4.8, 26.6, 
5.3, 12.9, 28.7, 0.4, 28.6, 6.2, 66.2, 26.7, 14.3, 7.5, 13.3, 
31.8, 2.7, 0, 3.6, 28.8, 1.6, 9.7, 17.2, 13.8, 14.6, 10, 10.8, 
12.7, 13.8, 26.8, 11, 34.9, 6.2, 62.2, 49.5, 2.7, 10, 14.5, 49.1, 
0, 1.5, 7.3, 30.3, 6.2, 15.3), continent = c("Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
"Europe", "Europe", "Europe", "Europe")), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -69L))

My aim was to get something like this (no interactive):

graph1

Or something like facets, but for each country.

graph2

Thank you very much for your attention.

CodePudding user response：

Data

votesharespop <- structure(list(country = c("Austria", "Belgium", "Bulgaria", 
                           "Czech Republic", "Denmark", "Estonia", "Finland", "France", 
                           "Germany", "Great Britain", "Greece", "Hungary", "Italy", "Lithuania", 
                           "Luxembourg", "Netherlands", "Poland", "Romania", "Portugal", 
                           "Slovakia", "Slovenia", "Spain", "Sweden", "Austria", "Belgium", 
                           "Bulgaria", "Czech Republic", "Denmark", "Estonia", "Finland", 
                           "France", "Germany", "Great Britain", "Greece", "Hungary", "Italy", 
                           "Lithuania", "Luxembourg", "Netherlands", "Poland", "Romania", 
                           "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden", "Austria", 
                           "Belgium", "Bulgaria", "Czech Republic", "Denmark", "Estonia", 
                           "Finland", "France", "Germany", "Great Britain", "Greece", "Hungary", 
                           "Italy", "Lithuania", "Luxembourg", "Netherlands", "Poland", 
                           "Romania", "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden"
), year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 
            2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 
            2009, 2009, 2009, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 
            2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 
            2014, 2014, 2014, 2014, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
            2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 
            2019, 2019, 2019, 2019, 2019), vote_share = c(17.3, 15.7, 16.7, 
                                                          4.3, 15.3, 0, 9.8, 8.1, 1.7, 22.7, 7.2, 71.2, 45.5, 12.2, 7.4, 
                                                          17, 27.4, 8.7, 0, 5.6, 35.2, 0, 3.3, 20.2, 7.6, 16.8, 4.8, 26.6, 
                                                          5.3, 12.9, 28.7, 0.4, 28.6, 6.2, 66.2, 26.7, 14.3, 7.5, 13.3, 
                                                          31.8, 2.7, 0, 3.6, 28.8, 1.6, 9.7, 17.2, 13.8, 14.6, 10, 10.8, 
                                                          12.7, 13.8, 26.8, 11, 34.9, 6.2, 62.2, 49.5, 2.7, 10, 14.5, 49.1, 
                                                          0, 1.5, 7.3, 30.3, 6.2, 15.3), continent = c("Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe", 
                                                                                                       "Europe", "Europe", "Europe", "Europe")), class = c("tbl_df", 
                                                                                                                                                           "tbl", "data.frame"), row.names = c(NA, -69L))

Code

library(ggplot2)
library(ggthemes) # to access theme_hc()

ggplot(data = votesharespop, mapping = aes(x = year, y = vote_share, color = country))   # specify data, x-axis, y-axis and grouping variable
  geom_line()   # a line per group
  geom_point()   # points per group
  theme_hc()    # a ggtheme, similar to your example
  labs(title = "Variation of vote shares of right wing populists, 2009 to 2019", # plot title
       subtitle = "Add a subtitle of your choice", # plot subtitle
       caption = "Add a caption of your choice")   # plot caption
  theme(legend.position = "right", # move legend to the right hand side of the plot
        axis.title.x = element_blank(), # remove x axis title
        axis.title.y = element_blank(), # remove y axis title
        legend.title = element_blank(), # remove legend title
        plot.title = element_text(size = 20, color = "gray40"), # change size and color of plot title
        plot.subtitle = element_text(color = "gray40"), # change color of subtitle
        plot.caption = element_text(color = "gray40", hjust = 0))   # change color of caption and left-align
  scale_y_continuous(breaks = seq(0, 80, by = 20))   # specify min, max and break distance for y axis
  scale_x_continuous(breaks = seq(2009, 2019, by = 5))   # specify min, max and break distance for x axis
  expand_limits(y = c(0, 80))

Output

Note however, that for multiple groups, the colors can be quite indistinguishable. It might be preferable to go with facet_wrap

Code

ggplot(data = votesharespop, mapping = aes(x = year, y = vote_share, color = country))   # specify data, x-axis, y-axis and grouping variable
  geom_line()   # a line per group
  geom_point()   # points per group
  theme_hc()    # a ggtheme, similar to your example
  labs(title = "Variation of vote shares of right wing populists, 2009 to 2019", # plot title
       subtitle = "Add a subtitle of your choice", # plot subtitle
       caption = "Add a caption of your choice")   # plot caption
  theme(legend.position = "right", # move legend to the right hand side of the plot
        axis.title.x = element_blank(), # remove x axis title
        axis.title.y = element_blank(), # remove y axis title
        legend.title = element_blank(), # remove legend title
        plot.title = element_text(size = 20, color = "gray40"), # change size and color of plot title
        plot.subtitle = element_text(color = "gray40"), # change color of subtitle
        plot.caption = element_text(color = "gray40", hjust = 0))   # change color of caption and left-align
  scale_y_continuous(breaks = seq(0, 75, by = 25))   # specify min, max and break distance for y axis
  scale_x_continuous(breaks = seq(2009, 2019, by = 5))   # specify min, max and break distance for x axis
  expand_limits(y = c(0, 75))   # adjust y axis limits
  facet_wrap(~ country)   # facet wrap
  theme(legend.position = "none")   # remove legend, since not needed anymore in facet_wrap
  theme(panel.spacing.x = unit(4, "mm")) # avoid overlapping of x axis text

Output