在 R 中，如何制作一个六条形图，其中每个条形包含一系列数据？

Question

我有一个电子表格，其中显示了棒球运动员的年龄和所参加的比赛。

structure(list(Player = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
12, 13, 14, 15, 16, 17, 18), Games = c(21, 7, 159, 156, 10, 152, 
23, 68, 13, 123, 29, 13, 111, 2, 84, 15, 140, 93), Age = c(34, 
23, 33, 22, 28, 24, 28, 33, 33, 29, 29, 25, 20, 41, 37, 21, 22, 
31), under21 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 
0, 0, 0), Y21to25 = c(0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 
0, 0, 1, 1, 0), Y26to30 = c(0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 
0, 0, 0, 0, 0, 0, 0), Y31to35 = c(1, 0, 1, 0, 0, 0, 0, 1, 1, 
0, 0, 0, 0, 0, 0, 0, 0, 1), Y36to40 = c(0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0), over40 = c(0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0)), row.names = c(NA, 18L), class = "data.frame")

这是使用 glimpse(df) 的另一个视图。出于说明目的，我添加了从“under21”到“over40”的六列。

Observations: 18
Variables: 9
$ Player  <dbl> 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18
$ Games   <dbl> 21, 7, 159, 156, 10, 152, 23, 68, 13, 123, 29, 13, 111, 2, 84…
$ Age     <dbl> 34, 23, 33, 22, 28, 24, 28, 33, 33, 29, 29, 25, 20, 41, 37, 2…
$ under21 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0
$ Y21to25 <dbl> 0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 1, 0
$ Y26to30 <dbl> 0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0
$ Y31to35 <dbl> 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1
$ Y36to40 <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0
$ over40  <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0

我需要的是一个条形图，其中有六个条形图（“under21”到“over40”）从 x 轴上升。 y 轴“游戏”将显示每个年龄组中所有玩家玩的游戏数量。因此，“under21”栏将显示所有 21 岁以下玩家的总游戏数，依此类推。

最好的方法是什么？

Answer 1

您可以使用tidyr 包（tidyverse 的一部分）中的pivot_longer 函数将数据框重新整形为更长的格式，过滤掉 0 个值，然后使用 @ 绘制它们所属类别的函数中的游戏总数987654326@:

library(tidyverse)
df %>% pivot_longer(-c(Player, Games, Age), names_to = "var", values_to = "val") %>%
  mutate(var = factor(var, levels = c("under21","Y21to25","Y26to30","Y31to35","Y36to40","over40"))) 
  
# A tibble: 108 x 5
   Player Games   Age var       val
    <dbl> <dbl> <dbl> <fct>   <dbl>
 1      1    21    34 under21     0
 2      1    21    34 Y21to25     0
 3      1    21    34 Y26to30     0
 4      1    21    34 Y31to35     1
 5      1    21    34 Y36to40     0
 6      1    21    34 over40      0
 7      2     7    23 under21     0
 8      2     7    23 Y21to25     1
 9      2     7    23 Y26to30     0
10      2     7    23 Y31to35     0
# … with 98 more rows

library(tidyverse)
df %>% pivot_longer(-c(Player, Games, Age), names_to = "var", values_to = "val") %>%
  mutate(var = factor(var, levels = c("under21","Y21to25","Y26to30","Y31to35","Y36to40","over40"))) %>%
  filter(val != 0) %>%
  ggplot(aes(x = var, y = Games, fill = var))+
  geom_col()

看起来是你想要达到的目标吗？

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编辑：计算ggplot2之外的游戏总和

您可以自己计算每个类别的游戏总数：

library(dplyr)
library(tidyr)
df %>% pivot_longer(-c(Player, Games, Age), names_to = "var", values_to = "val") %>%
  mutate(var = factor(var, levels = c("under21","Y21to25","Y26to30","Y31to35","Y36to40","over40"))) %>%
  filter(val != 0) %>%
  group_by(var) %>% 
  summarise(Games = sum(Games)) 

# A tibble: 6 x 2
  var     Games
  <fct>   <dbl>
1 under21   111
2 Y21to25   483
3 Y26to30   185
4 Y31to35   354
5 Y36to40   195
6 over40      2

您可以添加管道序列以直接绘制它：

library(dplyr)
library(tidyr)
library(gpglot2)
df %>% pivot_longer(-c(Player, Games, Age), names_to = "var", values_to = "val") %>%
  mutate(var = factor(var, levels = c("under21","Y21to25","Y26to30","Y31to35","Y36to40","over40"))) %>%
  filter(val != 0) %>%
  group_by(var) %>% 
  summarise(Games = sum(Games)) %>%
  ggplot(aes(x = var, y = Games, fill = var))+
  geom_col()

你会得到完全相同的情节

Answer 2

编辑 -- reshape2 已被 tidyr 取代。请参阅dc37's answer 了解更新的方法。

---

此解决方案使用reshape2 包中的melt 将年龄变量折叠成两列：variable 和value。从那里，您可以对数据框进行子集化以仅包含 value 为 1 的行，然后创建条形图，指定 stat = "identity" 以让 geom_bar 知道您是 supplying your own y value。

library(reshape2)
library(ggplot2)

stats <- structure(list(Player = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 
12, 13, 14, 15, 16, 17, 18), Games = c(21, 7, 159, 156, 10, 152, 
23, 68, 13, 123, 29, 13, 111, 2, 84, 15, 140, 93), Age = c(34, 
23, 33, 22, 28, 24, 28, 33, 33, 29, 29, 25, 20, 41, 37, 21, 22, 
31), under21 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 
0, 0, 0), Y21to25 = c(0, 1, 0, 1, 0, 1, 0, 0, 0, 0, 0, 1, 0, 
0, 0, 1, 1, 0), Y26to30 = c(0, 0, 0, 0, 1, 0, 1, 0, 0, 1, 1, 
0, 0, 0, 0, 0, 0, 0), Y31to35 = c(1, 0, 1, 0, 0, 0, 0, 1, 1, 
0, 0, 0, 0, 0, 0, 0, 0, 1), Y36to40 = c(0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0), over40 = c(0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0)), row.names = c(NA, 18L), class = "data.frame")

stats <- melt(stats, id.vars = c("Player","Games","Age"))
stats <- stats[stats$value == 1,]

p <-  ggplot(stats, aes(x = variable, y = Games))
p + geom_bar(stat = "identity") + xlab("")

此代码不考虑同时出现在under21 和Y36to40 组中的玩家13。