Top 20 National Football Teams by Goals Scored Animated Plot

From: https://github.com/basarabam/Top20AnimatedPlot

Animated plot of Top 20 National football teams by goals scored made by using ggplot2, gganimate and ggflags packages (and other listed). Follow comments in the code for instructions. 
This is how animated plot looks like, when finished:

Dataset: https://drive.google.com/open?id=1sTzf1ehIDBAUuRoUhQCUk_-S9YbXjCi93qMGoqAs7ec

#Loading packages
library(tidyverse)
library(lubridate)
library(countrycode)
library(gganimate)
library(ggflags)
library(tidyr)
library(viridis)

#Reading data
data_1 <- read_csv("results.csv")

#DATA PROCESSING
#-------------------------------------------------------
#Gathering scores
data <- data_1 %>%
        gather(score_playgr, score, -c(1:3, 6:9)) %>%
        gather(team_playgr, team, -c(1, 4:9))

#Cleaning gatherd values for removing duplicates       
data$team_playgr <- str_sub(data$team_playgr, 1, 4)
data$score_playgr <-str_sub(data$score_playgr, 1, 4)        

# Removing duplicates and adding year and month columns
data <- data %>%
        filter(team_playgr == score_playgr) %>%
        mutate(Year = year(date),
               Month = month(date)) %>%
        select(-score_playgr) %>%
        mutate_if(is.character, as.factor)

#Unique Years 
years_all <- unique(data$Year)

#Unique Countries
countries_unique <- data.frame(unique(data$team), stringsAsFactors = FALSE)
colnames(countries_unique) <- "team"
#Adding countrycode to countries, there is going to be a warning
#function country code cant find all countries and teritories
countries_unique$ccode <- tolower(countrycode(countries_unique$team, "country.name", "iso2c"))

#To add missing countrie codes, we need to add it by hand
missing_codes <- data.frame(team = c("England", "Scotland", "Wales",
                                     "Northern Ireland", "Yugoslavia",
                                     "Czechoslovakia"), 
                            ccode = c("gb-eng", "gb-sct", "gb-wls", 
                                      "gb-nir", "yu", "cz"), stringsAsFactors = FALSE)

#Adding missing codes(there must be a batter solution!)
countries_unique <- countries_unique %>% 
        left_join(missing_codes, by = c("team" = "team")) %>%
        mutate(ccode.x = replace_na(ccode.x, ""),
               ccode.y = replace_na(ccode.y, ""))%>%
        unite("ccode", c(ccode.x, ccode.y), sep = "") %>%
        mutate_if(is.character, as.factor)
        
# Creating data frame with each country for each year, to avoid animation jumps
all_y_c <- data.frame(expand.grid(Year = years_all, team = countries_unique$team)) %>%
        arrange(Year, team)

# Transforming dataset for ploting
data_test <- data %>%
        group_by(Year, team) %>%
        summarize(sum_score_y = sum(score)) %>%
        right_join(all_y_c, by = c("Year" = "Year", "team" = "team")) %>%
        mutate_at(c("sum_score_y"), ~replace(.,is.na(.),0)) %>%
        group_by(team, Year) %>%
        summarise(sum_t_goals = sum(sum_score_y)) %>%
        mutate(cum_y_goals = cumsum(sum_t_goals)) %>%
        #removing rows before first game
        filter(cum_y_goals != 0)

# Ranking function by year and adding counry code
ranking_f_y<- function(n){
        data_g <- data_test %>% 
                group_by(Year) %>%
                mutate(rank = min_rank(-cum_y_goals) * 1) %>%
                ungroup() %>%
                arrange(Year) %>%
                filter(rank <= n) %>%
                left_join(countries_unique, by = c("team" = "team")) %>%
                mutate(ccode = as.character(ccode),
                       team = as.character(team))
        
        data_g
}

#Ranking and coding countries
data_graph <- ranking_f_y(20)

# PLOTTING DATA
#-----------------------------------------

# Plotting 
p <- ggplot(data_graph, aes(rank, group = team, country = ccode, 
                     color = as.factor(team), fill = as.factor(team))) +
        geom_tile(aes(y = cum_y_goals/2,
                      height = cum_y_goals,
                      width = 0.9, fill = as.factor(team)), alpha = 0.6, color = NA)+
        geom_text(aes(y = 0, label = paste(team, " ")), vjust = 0.5, hjust = 1) +
        geom_text(aes(y = cum_y_goals + 275, label = paste(cum_y_goals, " ")))+
        geom_flag(aes(y = cum_y_goals + 85), size = 8)+
        scale_fill_viridis_d(option = "plasma", alpha = 1) +
        scale_color_viridis_d(option = "plasma", alpha = 1)+
        coord_flip(clip = "off", expand = FALSE) +
        scale_y_continuous(labels = scales::comma) +
        scale_x_reverse() +
        theme_minimal() +
        guides(color = FALSE, fill = FALSE) +
        labs(subtitle=paste0("Year: ",'{closest_state}'),
             title = "Top 20 National football teams by goals scored",
             caption = "Data source: https://www.kaggle.com/martj42/international-football-results-from-1872-to-2017\nPlot author: Milos Basaraba",
             x = "", y = "") +
        theme(plot.title = element_text(hjust = 0, vjust = 0, size = 12, color = plasma(1, alpha = 1)),
              plot.subtitle = element_text(hjust = 0, vjust = 0, size = 14, color = plasma(1, alpha = 1, begin = 0.4)),
              plot.caption = element_text(hjust = 0, vjust = 0, size = 8, color = plasma(1, alpha = 1, begin = 0.8)),
              panel.grid.major = element_blank(), panel.grid.minor = element_blank(),
              axis.ticks.y = element_blank(),  # These relate to the axes post-flip
              axis.text.y  = element_blank(),  # These relate to the axes post-flip
              axis.text.x = element_blank(),
              plot.margin = margin(1,1,1,4, "cm")) +
        #Adding transition states
        transition_states(Year, transition_length = 8, state_length = 1) +
        enter_fade() + 
        exit_shrink() +
        ease_aes('cubic-in-out')

# Animating plot
anim <- animate(p, fps = 25, duration = 60, width = 600, height = 400)

# Saving animation as gif
save_animation(anim, "output1.gif")