动画排序的条形图与酒吧互相超越

Moo*_*per 18 animation r data-visualization ggplot2 gganimate

你如何从R的Jaime Albella再现这张图表?

visualcapitalist.comtwitter上查看动画(如果有一个中断,请提供几个参考).

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我将其标记为ggplot2,gganimate但是可以从R生成的任何内容都是相关的.

数据(感谢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))
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Jon*_*ing 26

我已经根据相关问题调整了我的答案.我喜欢geom_tile用于动画条,因为它允许你滑动位置.

我在添加数据之前就已经开始研究了这个数据,但事实上,gapminder我使用的数据密切相关.

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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)
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Moo*_*per 8

到目前为止,这是我在很大程度上基于@Jon的答案提出的。

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)
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在此处输入图片说明

我可能会回来改善它。

可以通过删除实际网格并通过geom_segment在接近1000亿时更改alpha参数来使线移动和淡出来模拟移动网格。

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,通过一些小的外观更改,我们应该非常接近。


Nit*_*ish 6

这就是我提出的内容,我只使用Jon和Moody代码作为模板,而很少进行更改。

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"))
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每年的GDP变化 在这里,我使用持续时间40秒,这很慢。您可以更改持续时间,并根据需要使其更快或更慢。