lineplot via gganimate

gganimate extends the grammar of graphics as implemented by ggplot2 to animate of plots.
gganimate
R
ggplot2
lineplot
Author

Fazliddin Sultonov

Published

Oct 18, 2024

Load data from GitHub

Data Source: United Nations, Department of Economic and Social Affairs, Population Division (2018). World Urbanization Prospects: The 2018

Code 
df <- read.csv2("https://raw.githubusercontent.com/sultanovf/my_datasets/main/urban_population_19502025.csv")
years <- paste(1950:2025) #, sep=",", collapse= ","
years <- unlist(strsplit(years, ","))
new_cnames <- c("country",  years)
colnames(df) <- new_cnames
# Country names to plotting
countries <- c("Afghanistan", "Uzbekistan", "Kazakhstan", "Kyrgyzstan", "Tajikistan", "Turkmenistan","Russian Federation")

Data for Urban Population

Code 
df_urban <- df
df_urban |> 
  sample_n(3, replace = FALSE) |> 
  kable()
country 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Estonia 49.7 50.5 51.3 52.0 52.8 53.6 54.4 55.2 56.0 56.8 57.5 58.3 59.1 59.8 60.6 61.3 62.1 62.8 63.6 64.3 64.9 65.5 66.0 66.5 67.1 67.6 68.1 68.6 69.1 69.5 69.7 69.9 70.1 70.3 70.6 70.8 71.0 71.2 71.4 71.4 71.2 71.0 70.9 70.7 70.5 70.3 70.1 69.9 69.7 69.5 69.4 69.2 69.1 69.0 68.9 68.7 68.6 68.5 68.4 68.2 68.1 68.0 68.0 68.1 68.3 68.4 68.6 68.7 68.9 69.1 69.2 69.4 69.6 69.8 70.0 70.2
Zimbabwe 10.6 10.8 11.0 11.2 11.4 11.6 11.8 12.0 12.2 12.4 12.6 12.8 13.1 13.6 14.1 14.6 15.2 15.7 16.3 16.9 17.4 17.9 18.4 18.9 19.4 19.9 20.4 20.8 21.3 21.9 22.4 22.9 23.4 24.1 24.7 25.4 26.1 26.8 27.5 28.2 29.0 29.7 30.5 30.9 31.3 31.7 32.1 32.5 32.9 33.3 33.8 34.2 34.6 34.5 34.3 34.1 33.9 33.7 33.6 33.4 33.2 33.0 32.8 32.7 32.5 32.4 32.3 32.2 32.2 32.2 32.2 32.3 32.4 32.5 32.7 32.9
Antigua and Barbuda 30.1 31.0 32.0 32.9 33.9 34.9 35.9 36.9 37.9 39.0 39.7 39.0 38.4 37.8 37.2 36.6 36.0 35.4 34.8 34.2 33.8 33.9 34.0 34.1 34.1 34.2 34.3 34.4 34.5 34.5 34.6 34.7 34.8 34.9 34.9 35.0 35.1 35.2 35.3 35.3 35.4 35.5 35.1 34.7 34.3 34.0 33.6 33.2 32.9 32.5 32.1 31.7 31.1 30.5 29.8 29.2 28.6 28.0 27.4 26.8 26.2 25.7 25.5 25.4 25.2 25.0 24.8 24.7 24.6 24.5 24.4 24.4 24.3 24.3 24.3 24.4

Data for Rural Population

Code 
# new daf for rural, values = 100 - values
df_rural <- df # df rural

df_rural <-
  df_rural|> 
  mutate_if(is.numeric, fun <- function(x) 100-x)
# show
df_rural |> 
  sample_n(3, replace = FALSE) |> 
  kable()
country 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025
Germany 32.1 31.7 31.4 31.0 30.7 30.3 30.0 29.6 29.3 29.0 28.6 28.3 28.2 28.2 28.1 28.0 28.0 27.9 27.9 27.8 27.7 27.7 27.6 27.6 27.5 27.4 27.4 27.3 27.3 27.2 27.2 27.0 26.9 26.9 27.1 27.3 27.4 27.2 27.0 27.0 26.9 26.7 26.6 26.5 26.3 26.1 25.9 25.7 25.4 25.2 25.0 24.8 24.6 24.4 24.2 24.0 23.8 23.6 23.4 23.2 23.0 22.8 22.8 22.8 22.8 22.8 22.8 22.7 22.7 22.6 22.5 22.5 22.4 22.2 22.1 22.0
Belize 44.7 44.8 45.0 45.1 45.2 45.3 45.4 45.6 45.7 45.8 46.0 46.3 46.6 46.9 47.2 47.5 47.8 48.1 48.5 48.8 49.0 49.2 49.4 49.5 49.7 49.8 50.0 50.1 50.3 50.5 50.6 50.8 51.0 51.2 51.4 51.6 51.8 52.0 52.2 52.3 52.5 52.7 52.9 53.2 53.4 53.6 53.8 54.0 54.2 54.4 54.6 54.6 54.6 54.7 54.7 54.7 54.7 54.7 54.7 54.8 54.8 54.8 54.8 54.7 54.7 54.6 54.5 54.4 54.3 54.1 54.0 53.8 53.6 53.4 53.2 52.9
Denmark 32.0 31.7 31.4 31.0 30.7 30.4 29.6 28.8 28.0 27.1 26.3 25.6 24.9 24.2 23.6 23.0 22.4 21.8 21.3 20.8 20.3 19.8 19.3 18.8 18.3 17.9 17.4 17.1 16.8 16.6 16.3 16.1 16.0 15.9 15.8 15.6 15.5 15.4 15.3 15.2 15.2 15.1 15.1 15.1 15.0 15.0 15.0 15.0 14.9 14.9 14.9 14.8 14.8 14.6 14.4 14.1 13.9 13.7 13.5 13.3 13.2 13.0 12.9 12.7 12.6 12.5 12.4 12.2 12.1 12.0 11.9 11.8 11.6 11.5 11.4 11.2

Pivot table

Code 
# Pivot tables
pv_urban <- 
  df_urban |> 
  pivot_longer(
    cols = !country,
    names_to = "year",
    values_to = "urban"
  )

pv_rural <- 
  df_rural |> 
  pivot_longer(
    cols = !country,
    names_to = "year",
    values_to = "rural"
  )

df_merge <- left_join(pv_urban, pv_rural, by = c("country" ,"year"))
df_merge |> sample_n(6)
# show
# df_merge |> 
#   sample_n(size = 7, replace = FALSE) |> 
#   kable()
#> # A tibble: 6 × 4
#>   country                          year  urban rural
#>   <chr>                            <chr> <dbl> <dbl>
#> 1 United Arab Emirates             1991   78.9  21.1
#> 2 Armenia                          2003   64.1  35.9
#> 3 Gambia                           2022   63.9  36.1
#> 4 Qatar                            1967   87.6  12.4
#> 5 Montenegro                       1970   26.9  73.1
#> 6 Democratic Republic of the Congo 2009   39.5  60.5

Prepare DataFrame for plot

Code 
df_p <- df_merge |> 
  filter(
    country %in% countries
  ) |> 
  pivot_longer(
  cols = c(urban, rural),
  names_to = "pop",
  values_to = "pct"
  ) |> 
  mutate(year = as.integer(year)) # year must be integer for animated plotting(gganimate)
  # arrange(desc(year))

df_p |> sample_n(6)
#> # A tibble: 6 × 4
#>   country       year pop     pct
#>   <chr>        <int> <chr> <dbl>
#> 1 Uzbekistan    1968 urban  36.1
#> 2 Tajikistan    2007 rural  73.5
#> 3 Turkmenistan  2015 urban  50.3
#> 4 Tajikistan    1975 rural  64.5
#> 5 Tajikistan    2023 urban  28.2
#> 6 Kyrgyzstan    2019 urban  36.6

Lineplot facetted by countries

Code 
# Create plot facetted by countries
df_p |> 
  filter(country != "Russian Federation") |> 
  ggplot(aes(x = year, y = pct, color = pop)) +
  geom_line() +
  geom_point() + 
  transition_reveal(year) +
  scale_y_continuous(limits = c(0,100),breaks = seq(0, 100, 20),
                     labels = function(x) paste0(x, "%"),
                     ) +
  scale_x_continuous(limits = c(1950, 2025), breaks = seq(1950, 2025, 15)) +
  facet_wrap(~country) -> p_facetcountry
# facet_wrap(~country, labeller = labeller(country = new_labels)) -> p_facetcountry

# format plot
p_facetcountry <- p_facetcountry +
  labs(title = "Percentage of rural and urban population by selected countries",
       caption = "Source: United Nations, Department of Economic and Social Affairs",
       x = "Years, 1950 - 2025",
       y = "Percentage of Population") +
  theme(plot.title = element_text(color = "dodgerblue4", size = 12, face = "bold", hjust = 0.5),
        plot.caption = element_text(color = "dodgerblue", size = 8, face = "italic"),
        plot.background = element_rect(fill = "aliceblue"), 
        legend.title = element_blank(),
        legend.background = element_blank(),
        legend.position = "top")

p_facetcountry

# to save
#gganimate::animate(p_facetcountry, renderer = gifski_renderer(), height=500, width=700)

Lineplot facetted by Population (urban & rural)

Code 
# Create plot facetted by population
df_p |> 
  ggplot(aes(x = year, y = pct, color = country)) +
  geom_line() +
  geom_point() + 
  geom_text(aes(x = 2023, y = 96,
                label = "Made with \U1F49F by ФС"),
            stat = "unique",
            size = 2, color = "red") +
  # annotate("text", x=8, y=6, label= "Made by ©СФ") +
  transition_reveal(year) +
  scale_y_continuous(limits = c(0,100),breaks = seq(0, 100, 20),
                     labels = function(x) paste0(x, "%"),
  ) +
  scale_x_continuous(limits = c(1950, 2025), breaks = seq(1950, 2025, 5)) +
  facet_wrap(~pop, ncol = 1) -> p_facetpop

# format plot
p_facetpop +
  labs(title = "Urban countries bei Percentage of Population (urban & rural)",
       caption = "Source: United Nations, Department of Economic and Social Affairs",
       x = "Years, 1950 - 2025",
       y = "Percentage of Population") +
  theme(plot.title = element_text(color = "dodgerblue4", size = 12, face = "bold", hjust = 0.5),
        plot.caption = element_text(color = "dodgerblue", size = 8, face = "bold.italic"),
        plot.background = element_rect(fill = "aliceblue"), 
        legend.title = element_blank(),
        legend.background = element_blank(),
        legend.position = "bottom")

# To save
# animate(p_facetpop, renderer = gifski_renderer(), height=500, width=700)
# anim_save("C:/Users/sultanov/Documents/temp/gifs/p_facetpop.gif")

Lineplot for individual country (Uzbekistan)

Code 
# Uzbekistan
df_p |> 
  filter(country == "Uzbekistan") |> 
  ggplot(aes(x = year, y = pct, color = pop)) +
  geom_line() +
  geom_point() + 
  geom_text(aes(x = 2022, y = 98,
                label = "Made with \U1F49F by ФС"),
            stat = "unique",
            size = 2.5, color = "red") +
  transition_reveal(year) +
  scale_y_continuous(limits = c(0,100),breaks = seq(0, 100, 10),
                     labels = function(x) paste0(x, "%"),
  ) +
  # scale_x_continuous(limits = c(1950, 2025), breaks = seq(1950, 2025, 10),
  #                    expand = expansion(c(0.02, 0.02))) +
  scale_x_continuous(limits = c(1950, 2025), 
                     breaks = seq(1950, 2025, 5)) -> p_uz
 
# format plot
p_uz <- p_uz +
  labs(title = "Percentage of rural and urband Population in Uzbekistan, 1950-2025",
       caption = "Source: United Nations, Department of Economic and Social Affairs",
       x = "Years, 1950 - 2025",
       y = "Percentage of Population") +
  # annotate("text", x=2024, y=95, label= "Made by ©СФ") +   # adds text to the plot
  theme(plot.title = element_text(color = "dodgerblue4", size = 10, face = "bold", hjust = 0.5),
        plot.caption = element_text(color = "dodgerblue", size = 8, face = "bold.italic"),
        plot.background = element_rect(fill = "aliceblue"), 
        panel.background = element_rect(fill = "ghostwhite"),
        legend.title = element_blank(),
        legend.background = element_blank(),
        legend.position = "top")

p_uz
# To save
# animate(p_uz, renderer = gifski_renderer(), height=400, width=600)
# anim_save("C:/Users/sultanov/Documents/temp/gifs/p_uz.gif")

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