绘制多个数据集并将类别与条形图进行比较答案

【问题标题】：plot multiple datasets and compare categories with barplots绘制多个数据集并将类别与条形图进行比较
【发布时间】：2021-09-16 10:25:55
【问题描述】：

我有三个具有相同变量的数据集，我想比较三个数据集之间 29 个不同类别的一个变量。下面的示例应作为可重现的示例。我已经尝试过绘制它，但输出不如预期。我希望三个条彼此相邻，并在每个类别的图中都有一个小图。

number_trackers = c(1, 2, 3, 4, 5, 6), 
category = c("Ads", "Analytics", "Ads", "Analytics", "Ads", "Ads"), 
c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com"))

List_short_after=data.frame = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"), 
number_trackers = c(1, 2, 3, 4, 5, 6), 
category = c("Ads", "Analytics", "Ads", "Analytics", "Ads", "Ads"), 
c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com"))

List_after=data.frame = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"), 
number_trackers = c(1, 2, 3, 4, 5, 6), 
category = c("Ads", "Analytics", "Ads", "Analytics", "Ads", "Ads"), 
c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com")) 

ggplot(data = NULL, 
       mapping = aes(y = number_trackers,x=category)) +
  geom_col(data = List_before,fill= "#ca93ef", colour="#ca93ef") +
  geom_col(data = List_short_after,fill= "#5034c4", colour="#5034c4") +
  geom_col(data = List_after,fill= "#795fc6", colour="#795fc6") +
  facet_wrap(facets = vars(category))+
  theme_minimal() +
  theme(text = element_text(color = "#795fc6",size=12,face="bold"),
        axis.text = element_text(color = "#795fc6",size=14,face="bold"))+
  labs(  y = "Number Trackers", x = "Categories")

[![This is how the plot shut look like just with 3 bars instead of 2][1]][1]


  [1]: https://i.stack.imgur.com/nDq36.png

【问题讨论】：

标签： r dataframe ggplot2 plot

【解决方案1】：

以下代码可以帮助您实现目标。请注意，我对您的输入数据有些随意，因为您的问题似乎不完整。

library(ggplot2)

List_before <- data.frame(
  list_id = "list_before",
  name = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"),
  number_trackers = sample(c(1, 2, 3, 4, 5, 6)), 
  category = c("Ads", "Analytics", "Other 1", "Other 2", "Other 3", "Other 4"), 
  c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com"))

List_short_after <- data.frame(
  list_id = "list_short_after",
  name = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"),
  number_trackers = sample(c(1, 2, 3, 4, 5, 6)), 
  category = c("Ads", "Analytics", "Other 1", "Other 2", "Other 3", "Other 4"), 
  c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com"))

List_after <- data.frame(
  list_id = "list_after",
  name = c("Tracker1", "Tracker2", "Tracker3", "Tracker4","Tracker5","Tracker6"),
  number_trackers = sample(c(1, 2, 3, 4, 5, 6)),
  category = c("Ads", "Analytics", "Other 1", "Other 2", "Other 3", "Other 4"), 
  c4 = c("url1.com","ur2.com","url3.com","url4.com","url5.com","url6.com")) 

df <- rbind(List_before, List_short_after, List_after)

df$list_id <- as.factor(df$list_id)
df$category <- as.factor(df$category)

ggplot(df, aes(y = number_trackers, x = list_id)) +
  geom_bar(aes(fill = list_id), stat = "identity", position = position_dodge()) +
  theme(axis.text.x = element_blank(),
        axis.ticks.x = element_blank()) +
  facet_grid(~category) +
  labs(y = "Number of Trackers", x = NULL)

【讨论】：