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I am creating a bar chart race animation using geom_colh from the ggstance package. Right now, the animation is very choppy and doesn't appear to be one continuous animation, instead just one image after another. Below is what the current animation looks like:
Instead, I want the bars to "glide" from one position to another when they pass each other. Below is the reprex of the code I currently have:
library(tidyverse)
library(dplyr)
library(ggplot2)
library(gganimate)
library(ggstance)
library(zoo)
library(gifski)
library(shadowtext)
stats <- read_csv(url("https://raw.githubusercontent.com/samhoppen/Fantasy-Evaluator/main/Data/Animation%20Test%20Data.csv")) %>%
mutate(unique_id = paste0(player_name, recent_team))
all_weeks <- read_csv(url("https://raw.githubusercontent.com/samhoppen/Fantasy-Evaluator/main/Data/Animation%20Weeks%20Data.csv"))
NFL_pri <- stats$team_color
names(NFL_pri) <- stats$unique_id
NFL_sec <- stats$team_color2
names(NFL_sec) <- stats$unique_id
rb_ani <- ggplot(data = stats, aes(group = player_name)) +
geom_colh(aes(x = tot_fpts, y = rank, color = unique_id, fill = unique_id), position = 'identity',
size = 2, width = 0.8) +
scale_x_continuous(expand = expansion(mult = c(0, 0.05))) +
scale_y_reverse(expand = expansion(mult = c(0.01, 0.01)))+
geom_shadowtext(aes(x = name_loc, y = rank, label = player_name, color = unique_id),
bg.color = 'white', size = 5.5, na.rm = T, bg.r = 0.075, show.legend = FALSE) +
scale_color_manual(values = NFL_sec)+
scale_fill_manual(values = NFL_pri)+
labs(title = "Highest-scoring Fantasy Running Backs of the Past Decade",
subtitle = paste0("{all_weeks$week_name[as.numeric(previous_state)]}"),
caption = "Figure: #SamHoppen | Data: #nflfastR",
y = "",
x = "Total Fantasy Points")+
theme(legend.position = "none",
plot.title = element_text(size = 24, face = "bold", margin = margin(0,0,10,0)),
plot.subtitle = element_text(size = 12, margin = margin(0,0,10,0)),
plot.caption = element_text(size = 12)) +
transition_states(states = week_order, transition_length = 2, state_length = 1, wrap = F) +
view_follow(fixed_y = TRUE) +
enter_fly(y_loc = -21) +
exit_fly(y_loc = -21) +
ease_aes('linear')
anim <- animate(rb_ani, nframes = 100, fps = 5,renderer = gifski_renderer(), height = 900, width = 1600)
I've tried changing the transition length/state length, removing the theme items, removing the colors, removing the stat = 'identity' argument, changing the group variable, and the number of frames/fps. I'm at a loss of what to try next. Any suggestions would be great!
Part of the challenge here is very choppy rankings week to week. To make the animation smooth, you'll need to either make the animation pretty long, or select a subset of weeks to calculate rankings on. Here I've limited to just week 30-39, and added more frames.
I also did some more data cleaning to give all the players a rank in each week even if they aren't included in stats that week.
animate(
stats %>%
# Some week_name missing from stats, will use week_order to get from all_weeks
select(-week_name) %>%
left_join(all_weeks %>% select(week_order, week_name), by = "week_order") %>%
# add every week for each player, and fill in any missing tot_fpts or team_colors
select(week_order, week_name, player_name, tot_fpts,
unique_id, team_color, team_color2) %>%
complete(week_order, player_name) %>%
fill(tot_fpts, .direction = "down") %>%
fill(unique_id, team_color, team_color2, .direction = "downup") %>%
# only keep players who had >0 max_tot_fpts and weeks 30-39
group_by(player_name) %>%
mutate(max_tot_fpts = max(tot_fpts)) %>%
filter(max_tot_fpts > 0, week_order >= 30, week_order < 40) %>%
# smooth out tot_fpts
mutate(tot_fpts_smooth = spline(x = week_order, y = tot_fpts, xout = week_order)$y) %>%
# Calc rank for every week, only keep top 20
group_by(week_order) %>%
arrange(-tot_fpts_smooth, player_name) %>%
mutate(rank = row_number()) %>%
ungroup() %>%
filter(rank <= 20) %>%
ggplot(aes(group = player_name, y = rank)) +
geom_tile(aes(x = tot_fpts/2, height = 0.9, width = tot_fpts,
color = unique_id, fill = unique_id)) +
geom_shadowtext(aes(x = tot_fpts, y = rank, label = player_name, color = unique_id),
bg.color = 'white', size = 3.5, na.rm = T, bg.r = 0.075,
show.legend = FALSE, hjust = 1.1) +
# geom_text(aes(x = tot_fpts, label = paste(player_name, " ")), vjust = 0.2, hjust = 1) +
scale_y_reverse(breaks = 1:20, minor_breaks = NULL) +
scale_color_manual(values = NFL_sec)+
scale_fill_manual(values = NFL_pri)+
labs(title = "Highest-scoring Fantasy Running Backs of the Past Decade",
subtitle = paste0("{all_weeks$week_name[as.numeric(previous_state)]}"),
caption = "Figure: #SamHoppen | Data: #nflfastR",
y = "",
x = "Total Fantasy Points")+
theme_minimal() +
theme(legend.position = "none",
plot.title = element_text(size = 14, face = "bold", margin = margin(0,0,10,0)),
plot.subtitle = element_text(size = 12, margin = margin(0,0,10,0)),
plot.caption = element_text(size = 12)) +
transition_states(week_order, state_length = 0) +
view_follow(fixed_y = TRUE) +
enter_fly(y_loc = -21) +
exit_fly(y_loc = -21) +
ease_aes('linear'),
fps = 20, duration = 4, width = 400, height = 300)
Not specific to any particular piece of code, is there a relatively straightforward way to change the color of the text in a geom_label_repel box?
Specifically, I have code that produces the below chart
The percentage in the label box is the percent change in 7-day moving average for the most recent week over the week prior. I'd simply like to color the text red when the value is positive and green when it is negative.
The dataframe for this chart can be copied from here.
The plot code is
#endpoint layer
BaseEndpoints <- smDailyBaseData %>% filter(Base %in% AFMCbases) %>%
group_by(Base) %>%
filter(DaysSince == max(DaysSince)) %>%
select(Base, abbv, DaysSince, newRate,label) %>%
ungroup()
ZoomEndpoints <- BaseEndpoints %>% filter(Base != 'Edwards') %>%
mutate(zoom = TRUE)
CAEndPoint <- BaseEndpoints %>% filter(Base == 'Edwards') %>%
mutate(zoom = FALSE)
ZoomEndpoints <- rbind(ZoomEndpoints, CAEndPoint)
BasePlot <- smDailyBaseData %>% filter(Base %in% AFMCbases) %>%
ggplot(mapping = aes(x = as.numeric(DaysSince), y = newRate)) +
geom_line(aes(color=abbv),show.legend = FALSE) +
scale_color_ucscgb() +
geom_point(data = BaseEndpoints,size = 1.5,shape = 21,
aes(color = abbv,fill = abbv), show.legend = FALSE) +
geom_label_repel(data=ZoomEndpoints, aes(label=label), show.legend = FALSE,
vjust = 0, xlim=c(105,200), size=3, direction='y') +
labs(x = "Days Since First Confirmed Case",
y = "% Local Population Infected Daily") +
theme(plot.title = element_text(size = rel(1), face = "bold"),
plot.subtitle = element_text(size = rel(0.7)),
plot.caption = element_text(size = rel(1))) +
facet_zoom(xlim = c(50,120), ylim=c(0,0.011),zoom.data=zoom)
print(BasePlot)
Yes, it's as simple as this:
library(ggplot2)
df <- data.frame(x = c(-1, -1, 1, 1), y = c(-1, 1, 1, -1), value = c(-2, -1, 1, 2))
ggplot(df, aes(x, y)) +
geom_point(size = 3) +
ggrepel::geom_label_repel(aes(label = value, colour = factor(sign(value)))) +
lims(x = c(-100, 100), y = c(-100, 100)) +
scale_colour_manual(values = c("red", "forestgreen"))
EDIT
Now we have a more concrete example, I can see the problem more clearly. There are workarounds such as using ggnewscale or a hand-crafted solution such as Ian Campbell's thorough example. Personally, I would just note that you haven't used the fill scale yet, and this looks pretty good to my eye:
Here's a bit of a hacky solution since you can't have two scale_color_*'s at the same time:
The approach centers on manually assigning the color outside of aes in the geom_label_repel call. Adding one to the grepl result that searches for the minus sign in the label allows you to subset the two colors. You need two colors for each label, I assume for the box and for the text, so I used rep.
smDailyBaseData %>%
ggplot(mapping = aes(x = as.numeric(DaysSince), y = newRate)) +
geom_line(aes(color=abbv),show.legend = FALSE) +
scale_color_ucscgb() +
geom_point(data = BaseEndpoints,size = 1.5,shape = 21,
aes(color = abbv,fill = abbv), show.legend = FALSE) +
geom_label_repel(data=ZoomEndpoints, aes(label=label),
color = rep(c("green","red")[1+grepl("\\-\\d",as.factor(ZoomEndpoints$label))],times = 2),
show.legend = FALSE, vjust = 0, xlim=c(105,200),
size=3, direction='y') +
labs(x = "Days Since First Confirmed Case",
y = "% Local Population Infected Daily") +
theme(plot.title = element_text(size = rel(1), face = "bold"),
plot.subtitle = element_text(size = rel(0.7)),
plot.caption = element_text(size = rel(1))) +
facet_zoom(xlim = c(50,120), ylim=c(0,0.011),zoom.data=zoom)
Data Setup
#source("https://pastebin.com/raw/Vn2abQ4a")
BaseEndpoints <- smDailyBaseData %>%
group_by(Base) %>%
dplyr::filter(DaysSince == max(DaysSince)) %>%
dplyr::select(Base, abbv, DaysSince, newRate,label) %>%
ungroup()
ZoomEndpoints <- BaseEndpoints %>% filter(Base != 'Edwards') %>%
mutate(zoom = TRUE)
CAEndPoint <- BaseEndpoints %>% filter(Base == 'Edwards') %>%
mutate(zoom = FALSE)
ZoomEndpoints <- rbind(ZoomEndpoints, CAEndPoint)
My goal is to produce labels with commas, but no decimals. Let's say I have a ggplot with the following section:
geom_text(aes(y = var,
label = scales::comma(round(var))), hjust = 0, nudge_y = 300 )
This is almost what I need. It gives me the commas, but has a decimal. I have seen here (axis labels with comma but no decimals ggplot) that comma_format() could be good, but I think the label in my case needs a data argument, which comma_format() does not take. What can I do?
Update:
As an example of when this problem occurs, see the following, which uses gganimate and has a lot more going on. Code derived from Jon Spring's answer at Animated sorted bar chart with bars overtaking each other
library(gapminder)
library(gganimate)
library(tidyverse)
gap_smoother <- gapminder %>%
filter(continent == "Asia") %>%
group_by(country) %>%
complete(year = full_seq(year, 1)) %>%
mutate(gdpPercap = spline(x = year, y = gdpPercap, xout = year)$y) %>%
group_by(year) %>%
mutate(rank = min_rank(-gdpPercap) * 1) %>%
ungroup() %>%
group_by(country) %>%
complete(year = full_seq(year, .5)) %>%
mutate(gdpPercap = spline(x = year, y = gdpPercap, xout = year)$y) %>%
mutate(rank = approx(x = year, y = rank, xout = year)$y) %>%
ungroup() %>%
arrange(country,year)
gap_smoother2 <- gap_smoother %>% filter(year<=2007 & year>=1999)
gap_smoother3 <- gap_smoother2 %<>% filter(rank<=8)
p <- ggplot(gap_smoother3, aes(rank, group = country,
fill = as.factor(country), color = as.factor(country))) +
geom_tile(aes(y = gdpPercap/2,
height = gdpPercap,
width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = 0, label = paste(country, " ")), vjust = 0.2, hjust = 1) +
geom_text(aes(y = gdpPercap,
label = scales::comma(round(gdpPercap))), hjust = 0, nudge_y = 300 ) +
coord_flip(clip = "off", expand = FALSE) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title='{closest_state %>% as.numeric %>% floor}',
x = "", y = "GFP per capita") +
theme(plot.title = element_text(hjust = 0, size = 22),
axis.ticks.y = element_blank(), # These relate to the axes post-flip
axis.text.y = element_blank(), # These relate to the axes post-flip
plot.margin = margin(1,1,1,4, "cm")) +
transition_states(year, transition_length = 1, state_length = 0) +
enter_grow() +
exit_shrink() +
ease_aes('linear')
animate(p, fps = 2, duration = 5, width = 600, height = 500)
In addition to the solution provided by #drf, you need to add scale_y_continuous(scales::comma) to your ggplot commands. But put it before the coord_flip function.
p <- ggplot(gap_smoother3, aes(rank, group = country,
fill = as.factor(country), color = as.factor(country))) +
geom_tile(aes(y = gdpPercap/2,
height = gdpPercap,
width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = gdpPercap,
label = scales::comma(round(gdpPercap), accuracy=1)),
hjust = 0, nudge_y = 300 ) +
scale_y_continuous(labels = scales::comma) +
... etc.
I created an animated bar plot displaying goals scored by players (fictional).
Please see the reproduced data for the example:
df <- data.frame(Player = rep(c("Aguero", "Salah", "Aubameyang", "Kane"), 6),
Team = rep(c("ManCity", "Liverpool", "Arsenal", "Tottenham"), 6),
Gameday = c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6,6),
Goals = c(0,1,2,0,1,1,3,1,2,1,3,2,2,2,4,3,3,2,4,5,5,3,5,6),
stringsAsFactors = F)
Following animated bar plot are created by the code below.
# loading required
library(tidyverse)
library(gganimate)
library(png)
Edited:
I would like to include following icons for each player:
icon1.png <- image_read('https://raw.githubusercontent.com/sialbi/examples/master/player1.png')
icon2.png <- image_read('https://raw.githubusercontent.com/sialbi/examples/master/player2.png')
icon3.png <- image_read('https://raw.githubusercontent.com/sialbi/examples/master/player3.png')
icon4.png <- image_read('https://raw.githubusercontent.com/sialbi/examples/master/player4.png')
gap <- df %>%
group_by(Gameday) %>%
mutate(rank = min_rank(-Goals) * 1,
Value_rel = Goals/Goals[rank==1],
Value_lbl = paste0(" ", Goals)) %>%
filter(rank <=10) %>%
ungroup()
gap %>%
group_by(Player) %>%
arrange(Gameday) %>%
mutate(prev.rank = lag(rank)) %>%
ungroup() %>%
group_by(Gameday) %>%
arrange(rank, prev.rank) %>%
mutate(x = seq(1, n())) %>%
ungroup() %>%
ggplot(aes(x = x, y = Goals, fill = Player, color = Player)) +
geom_col() +
geom_text(aes(y = 0, label = Player), size = 5, color="black", hjust = -0.05) +
geom_text(aes(label = Value_lbl), hjust = 0) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title = "Gameday: {closest_state}", x="", y = "Goals scored") +
theme(plot.title = element_text(hjust = 0, size = 26),
axis.ticks.y = element_blank(),
axis.text.y = element_blank(),
plot.margin = margin(1,1,1,4, "cm")) +
transition_states(Gameday, transition_length = 4, state_length = 1) +
ease_aes('cubic-in-out')
Problem
To complete the animation I would like to include a picture of each player on the y axis. Below I edited the animation to display the desired result (the circles were chosen to avoid violating any copyrights).
The images (circles) should also move up and down as the bars.
Is there are way to include images on the y-axis?
Edited Code
After the presented suggestions I was able to fix the problems. The code below is working accordingly.
library(imager)
library(ggimage)
library(magick)
library(tidyverse)
library(gganimate)
library(png)
library(gapminder)
#read data
df <- data.frame(Player = rep(c("Aguero", "Salah", "Aubameyang", "Kane"), 6),
Team = rep(c("ManCity", "Liverpool", "Arsenal", "Tottenham"), 6),
Gameday = c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5,6,6,6,6),
Goals = c(0,1,2,0,1,1,3,1,2,1,3,2,2,2,4,3,3,2,4,5,5,3,5,6),
stringsAsFactors = F)
# import images
df2 <- data.frame(Player = c("Aguero", "Salah", "Aubameyang", "Kane"),
Image = sample(c("https://raw.githubusercontent.com/sialbi/examples/master/player1.png",
"https://raw.githubusercontent.com/sialbi/examples/master/player2.png",
"https://raw.githubusercontent.com/sialbi/examples/master/player3.png",
"https://raw.githubusercontent.com/sialbi/examples/master/player4.png")),
stringsAsFactors = F)
gap <- df %>%
group_by(Gameday) %>%
mutate(rank = min_rank(-Goals) * 1,
Value_rel = Goals/Goals[rank==1],
Value_lbl = paste0(" ", Goals)) %>%
filter(rank <=10) %>%
ungroup()
p = gap %>%
left_join(df2, by = "Player") %>% # add image file location to the dataframe being
group_by(Player) %>%
arrange(Gameday) %>%
mutate(prev.rank = lag(rank)) %>%
ungroup() %>%
group_by(Gameday) %>%
arrange(rank, prev.rank) %>%
mutate(x = seq(1, n())) %>%
ungroup()
ggplot(p, aes(x = x, y = Goals, fill = Player, color = Player)) +
geom_col() +
geom_text(aes(y = 0, label = Player), size = 5, color="black", hjust = -0.05) +
geom_text(aes(label = Value_lbl), hjust = 0) +
# where the error occurs
geom_image(aes(x = x, Image = Image), y = 0,
size = 0.25, hjust = 1,
inherit.aes = FALSE) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title = "Gameday: {closest_state}", x = "", y = "Goals scored") +
theme_classic() +
theme(plot.title = element_text(hjust = 0, size = 26),
axis.ticks.y = element_blank(),
axis.text.y = element_blank(),
plot.margin = margin(1, 1, 1, 4, "cm")) +
transition_states(Gameday, transition_length = 4, state_length = 1) +
ease_aes('cubic-in-out')
You can try the following:
Step 0. Create png images for use, because I don't want to worry about copyright violations either.
emoji.list <- c("grinning", "smile", "heart_eyes", "smirk")
for(i in seq_along(emoji.list)) {
ggsave(paste0("icon", i, ".png"),
ggplot() +
emojifont::geom_emoji(alias = emoji.list[i], size = 10, vjust = 0.5) +
theme_void(),
width = 0.4, height = 0.4, units = "in")
}
rm(emoji.list, i)
Step 1. Create a data frame mapping each player to the location of his image file.
df2 <- data.frame(Player = c("Aguero", "Salah", "Aubameyang", "Kane"),
Image = c("icon1.png", "icon2.png", "icon3.png", "icon4.png"),
stringsAsFactors = F)
Step 2. Add image to plot in a new geom_image layer, & animate everything as before.
library(ggimage)
gap %>%
left_join(df2, by = "Player") %>% # add image file location to the dataframe being
# passed to ggplot()
group_by(Player) %>%
arrange(Gameday) %>%
mutate(prev.rank = lag(rank)) %>%
ungroup() %>%
group_by(Gameday) %>%
arrange(rank, prev.rank) %>%
mutate(x = seq(1, n())) %>%
ungroup() %>%
ggplot(aes(x = x, y = Goals, fill = Player, color = Player)) +
geom_col() +
geom_text(aes(y = 0, label = Player), size = 5, color="black", hjust = -0.05) +
geom_text(aes(label = Value_lbl), hjust = 0) +
geom_image(aes(x = x, image = Image), y = 0, # add geom_image layer
size = 0.25, hjust = 1,
inherit.aes = FALSE) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title = "Gameday: {closest_state}", x = "", y = "Goals scored") +
theme_classic() +
theme(plot.title = element_text(hjust = 0, size = 26),
axis.ticks.y = element_blank(),
axis.text.y = element_blank(),
plot.margin = margin(1, 1, 1, 4, "cm")) +
transition_states(Gameday, transition_length = 4, state_length = 1) +
ease_aes('cubic-in-out')
Edit: keyword is 'bar chart race'
How would you go at reproducing this chart from Jaime Albella in R ?
See the animation on visualcapitalist.com or on twitter (giving several references in case one breaks).
I'm tagging this as ggplot2 and gganimate but anything that can be produced from R is relevant.
data (thanks to https://github.com/datasets/gdp )
gdp <- read.csv("https://raw.github.com/datasets/gdp/master/data/gdp.csv")
# remove irrelevant aggregated values
words <- scan(
text="world income only total dividend asia euro america africa oecd",
what= character())
pattern <- paste0("(",words,")",collapse="|")
gdp <- subset(gdp, !grepl(pattern, Country.Name , ignore.case = TRUE))
Edit:
Another cool example from John Murdoch :
Most populous cities from 1500 to 2018
Edit: added spline interpolation for smoother transitions, without making rank changes happen too fast. Code at bottom.
I've adapted an answer of mine to a related question. I like to use geom_tile for animated bars, since it allows you to slide positions.
I worked on this prior to your addition of data, but as it happens, the gapminder data I used is closely related.
library(tidyverse)
library(gganimate)
library(gapminder)
theme_set(theme_classic())
gap <- gapminder %>%
filter(continent == "Asia") %>%
group_by(year) %>%
# The * 1 makes it possible to have non-integer ranks while sliding
mutate(rank = min_rank(-gdpPercap) * 1) %>%
ungroup()
p <- ggplot(gap, aes(rank, group = country,
fill = as.factor(country), color = as.factor(country))) +
geom_tile(aes(y = gdpPercap/2,
height = gdpPercap,
width = 0.9), alpha = 0.8, color = NA) +
# text in x-axis (requires clip = "off" in coord_*)
# paste(country, " ") is a hack to make pretty spacing, since hjust > 1
# leads to weird artifacts in text spacing.
geom_text(aes(y = 0, label = paste(country, " ")), vjust = 0.2, hjust = 1) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title='{closest_state}', x = "", y = "GFP per capita") +
theme(plot.title = element_text(hjust = 0, size = 22),
axis.ticks.y = element_blank(), # These relate to the axes post-flip
axis.text.y = element_blank(), # These relate to the axes post-flip
plot.margin = margin(1,1,1,4, "cm")) +
transition_states(year, transition_length = 4, state_length = 1) +
ease_aes('cubic-in-out')
animate(p, fps = 25, duration = 20, width = 800, height = 600)
For the smoother version at the top, we can add a step to interpolate the data further before the plotting step. It can be useful to interpolate twice, once at rough granularity to determine the ranking, and another time for finer detail. If the ranking is calculated too finely, the bars will swap position too quickly.
gap_smoother <- gapminder %>%
filter(continent == "Asia") %>%
group_by(country) %>%
# Do somewhat rough interpolation for ranking
# (Otherwise the ranking shifts unpleasantly fast.)
complete(year = full_seq(year, 1)) %>%
mutate(gdpPercap = spline(x = year, y = gdpPercap, xout = year)$y) %>%
group_by(year) %>%
mutate(rank = min_rank(-gdpPercap) * 1) %>%
ungroup() %>%
# Then interpolate further to quarter years for fast number ticking.
# Interpolate the ranks calculated earlier.
group_by(country) %>%
complete(year = full_seq(year, .5)) %>%
mutate(gdpPercap = spline(x = year, y = gdpPercap, xout = year)$y) %>%
# "approx" below for linear interpolation. "spline" has a bouncy effect.
mutate(rank = approx(x = year, y = rank, xout = year)$y) %>%
ungroup() %>%
arrange(country,year)
Then the plot uses a few modified lines, otherwise the same:
p <- ggplot(gap_smoother, ...
# This line for the numbers that tick up
geom_text(aes(y = gdpPercap,
label = scales::comma(gdpPercap)), hjust = 0, nudge_y = 300 ) +
...
labs(title='{closest_state %>% as.numeric %>% floor}',
x = "", y = "GFP per capita") +
...
transition_states(year, transition_length = 1, state_length = 0) +
enter_grow() +
exit_shrink() +
ease_aes('linear')
animate(p, fps = 20, duration = 5, width = 400, height = 600, end_pause = 10)
This is what I came up with, so far, based in good part on #Jon's answer.
p <- gdp %>%
# build rank, labels and relative values
group_by(Year) %>%
mutate(Rank = rank(-Value),
Value_rel = Value/Value[Rank==1],
Value_lbl = paste0(" ",round(Value/1e9))) %>%
group_by(Country.Name) %>%
# keep top 10
filter(Rank <= 10) %>%
# plot
ggplot(aes(-Rank,Value_rel, fill = Country.Name)) +
geom_col(width = 0.8, position="identity") +
coord_flip() +
geom_text(aes(-Rank,y=0,label = Country.Name,hjust=0)) + #country label
geom_text(aes(-Rank,y=Value_rel,label = Value_lbl, hjust=0)) + # value label
theme_minimal() +
theme(legend.position = "none",axis.title = element_blank()) +
# animate along Year
transition_states(Year,4,1)
animate(p, 100, fps = 25, duration = 20, width = 800, height = 600)
I might come back to improve it.
The moving grid could be simulated by removing the actual grid and having geom_segment lines moving and fading out thanks to an alpha parameter changing when it approaches 100 billion.
To have labels changing values between years (which gives a nice feeling of urgency in the original chart) I think we have no choice but multiplying the rows while interpolating labels, we'll need to interpolate Rank too.
Then with a few minor cosmetic changes we should be pretty close.
This is what I came up, I just use Jon and Moody code as a template and make few changes.
library(tidyverse)
library(gganimate)
library(gapminder)
theme_set(theme_classic())
gdp <- read.csv("https://raw.github.com/datasets/gdp/master/data/gdp.csv")
words <- scan(
text="world income only total dividend asia euro america africa oecd",
what= character())
pattern <- paste0("(",words,")",collapse="|")
gdp <- subset(gdp, !grepl(pattern, Country.Name , ignore.case = TRUE))
colnames(gdp) <- gsub("Country.Name", "country", colnames(gdp))
colnames(gdp) <- gsub("Country.Code", "code", colnames(gdp))
colnames(gdp) <- gsub("Value", "value", colnames(gdp))
colnames(gdp) <- gsub("Year", "year", colnames(gdp))
gdp$value <- round(gdp$value/1e9)
gap <- gdp %>%
group_by(year) %>%
# The * 1 makes it possible to have non-integer ranks while sliding
mutate(rank = min_rank(-value) * 1,
Value_rel = value/value[rank==1],
Value_lbl = paste0(" ",value)) %>%
filter(rank <=10) %>%
ungroup()
p <- ggplot(gap, aes(rank, group = country,
fill = as.factor(country), color = as.factor(country))) +
geom_tile(aes(y = value/2,
height = value,
width = 0.9), alpha = 0.8, color = NA) +
geom_text(aes(y = 0, label = paste(country, " ")), vjust = 0.2, hjust = 1) +
geom_text(aes(y=value,label = Value_lbl, hjust=0)) +
coord_flip(clip = "off", expand = FALSE) +
scale_y_continuous(labels = scales::comma) +
scale_x_reverse() +
guides(color = FALSE, fill = FALSE) +
labs(title='{closest_state}', x = "", y = "GDP in billion USD",
caption = "Sources: World Bank | Plot generated by Nitish K. Mishra #nitishimtech") +
theme(plot.title = element_text(hjust = 0, size = 22),
axis.ticks.y = element_blank(), # These relate to the axes post-flip
axis.text.y = element_blank(), # These relate to the axes post-flip
plot.margin = margin(1,1,1,4, "cm")) +
transition_states(year, transition_length = 4, state_length = 1) +
ease_aes('cubic-in-out')
animate(p, 200, fps = 10, duration = 40, width = 800, height = 600, renderer = gifski_renderer("gganim.gif"))
Here I am using duration 40 second, which is slow. You can change duration and make it faster or slower as you needed.