Question

您将如何从R中的Jaime Albella复制此图表？

在visualcapitalist.com或twitter上观看动画（以防万一，给几个参考）。

我将其标记为 ggplot2 和 gganimate ，但是可以用R生成的任何东西都是相关的。

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))

编辑：

约翰·默多克（John Murdoch）的另一个不错的例子：

Most populous cities from 1500 to 2018

Answer 1

我改编了我的答案to a related question。我喜欢将geom_tile用于动画条，因为它可以让您滑动位置。

在添加数据之前，我已经进行了此工作，但是碰巧，我使用的gapminder数据是密切相关的。

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)

Answer 2

到目前为止，这是我根据@Jon的回答得出的。

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)

我可能会回来改进它。

可以通过删除实际的网格并通过geom_segment线的移动和淡出来模拟移动的网格，这要归功于alpha参数在接近1000亿时发生变化。

要让标签在几年之间更改值（这在原始图表中给人以紧迫感），我认为我们别无选择，只能在插值标签时乘以行，我们也需要插值Rank。

然后进行一些小小的外观更改，我们应该非常接近。

Answer 3

这就是我的想法，我只是使用Jon和Moody代码作为模板，并且进行了一些更改。

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"))

GDP changes per year 在这里，我使用持续时间40秒，这很慢。您可以根据需要更改持续时间，以使其更快或更慢。

动画排序的条形图，条形相互超越

3 个答案: