Bar Chart Race/Bar Chart Animation in R

R is a very powerful software for data visualization. In this  post, I present a simple case of how data can be visualized in Bar Chart Race in R. I have used the COVID cases data by country and showed the evolution of COVID cases in the 10 most affected countries during the last 350 days. 

rm(list=ls())  # removes the existing objects from the environment.  

# library used

library(tidyverse)
library(readxl)
library(dplyr)
library(gganimate) 

# setting working directory
setwd('C:/Users/siddhabhatta/Desktop/October31')
# data source : https://www.ecdc.europa.eu/en/covid-19/data

# importing data 

The data and R script can be downloaded from the link below:

https://drive.google.com/drive/folders/1HkPFE7v4fIx2rOOJnhE1E52rCQlGkigq?usp=sharing

 data=read_excel('coviddec14.xlsx')
  # first few observations

head(data)

# creating a new date variable with standard date format

 data$date<-as.Date(data$dateRep, format="%m/%d/%y")
head(data$date)
 # Making the country names short

data$country[data$country=="United_States_of_America"]<-"USA"
data$country[data$country=="United_Kingdom"]<-"UK"
data$country[data$country=="Cases_on_an_international_conveyance_Japan"]<-"Intl_CV_Center_Japan"   

#groupoing the data by country and date and finding cumulated total of cases per day
datanew<-data %>% # %>%  can be read as then   
  select(country, cases, date, continent) %>%  
   group_by(continent, country, date) %>%
  summarise(total=sum(cases)) %>%
  mutate(cumtotal=cumsum(total))
 # prepare data by ranks and filter the top 10 countries
 data2=datanew %>%
   group_by(date) %>%
   arrange(date, -cumtotal) %>%  
   mutate(rank = 1:n()) %>%  
  filter(rank <= 10)
# producing the static 350 ggplots 

data2 %>%  
  ggplot()+  
  aes(xmin = 0 ,  
      xmax = cumtotal) +  
  aes(ymin = rank - 0.45,  
      ymax = rank + 0.45,  
      y = rank) +  
  facet_wrap(~ date) +  
  geom_rect(alpha = .7) +  
  aes(fill = continent) +  
  scale_fill_viridis_d(option = "magma",  
                       direction = -1) +  
  scale_x_continuous(  
    limits = c(-5000000, 16000000),  
    breaks = c(-5000000, 0, 4000000, 8000000, 12000000, 16000000)) +  
  geom_text(col = "darkblue",  
            hjust = "right",  
            aes(label = country),  
            x = -100) +
  geom_text(col = "darkblue",  
            hjust = "right",  
            aes(label = paste(cumtotal), x=12000000)) +
    scale_y_reverse() +  
  labs(fill = NULL) +
  ggtitle("Evolution of Covid-19 Cases")+
  labs(x = "Covid Cases") +  
  labs(y = "Top 10 Countries") +  
  theme_classic() ->  
  my_plot
# saves the plot in the object my_plot

# animate the 350 frames by date and save it as p

 p<-my_plot +  
  facet_null() +  
  geom_text(x = 8000000 , y = -10,  
            family = "Times",  
            aes(label = as.character(date)),  
            size = 12, col = "green") +
    aes(group = country) +  
 transition_time(date)

#Animate p with total 350 frames and 5 frames per second

 animate(p, nframes=350, fps=5, width=1000)

Saving the results as gif format 

 gif<- animate(p, fps = 5,  width = 1000, height = 700,
        renderer = gifski_renderer("gganim.gif"), end_pause = 15, start_pause =  15)
anim_save("gganim.gif", animation = gif )
 

 Here is the output.

 And here is the video explanation.