R 如何将数据分组，然后在ggplot2中绘制条形图

我有数据帧df和3列，例如

NUMERIC1:      NUMERIC2:      GROUP(CHARACTER):
100            1               A
200            2               B
300            3               C
400            4               A

我想按GROUPCHARACTER对NUMERIC1进行分组，然后计算每组的平均值。 诸如此类：

mean(NUMERIC1):  GROUP(CHARACTER):
250                  A
200                  B
300                  C

最后，我想使用ggplot2绘制条形图，其中x轴上有GROUPCHARACTER，y轴上有meanNUMERIC。 它应该是这样的：

我曾经

mean <- tapply(df$NUMERIC1, df$GROUP(CHARACTER), FUN=mean)

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但我不确定是否可以，即使可以，我也不知道下一步该怎么办。

我建议如下：

#Imports; data.table, which allows for really convenient "apply a function to
#"each part of a df, by unique value", and ggplot2
library(data.table)
library(ggplot2)

#Convert df to a data.table. It remains a data.frame, so any function that works
#on a data.frame can still work here.
data <- as.data.table(df)

#By each unique value in "CHARACTER", subset and calculate the mean of the
#NUMERIC1 values within that subset. You end up with a data.frame/data.table
#with the columns CHARACTER and mean_value
data <- data[, j = list(mean_value = mean(NUMERIC1)), by = "CHARACTER"]

#And now we play the plotting game (the plotting game is boring, lets
#play Hungry Hungry Hippos!)
plot <- ggplot(data, aes(CHARACTER, mean_value)) + geom_bar()

#And that should do it.

res <- aggregate(NUMERIC1 ~ GROUP, data = df, FUN = mean)
ggplot(res, aes(x = GROUP, y = NUMERIC1)) + geom_bar(stat = "identity")

尝试以下方法：

#Imports; data.table, which allows for really convenient "apply a function to
#"each part of a df, by unique value", and ggplot2
library(data.table)
library(ggplot2)

#Convert df to a data.table. It remains a data.frame, so any function that works
#on a data.frame can still work here.
data <- as.data.table(df)

#By each unique value in "CHARACTER", subset and calculate the mean of the
#NUMERIC1 values within that subset. You end up with a data.frame/data.table
#with the columns CHARACTER and mean_value
data <- data[, j = list(mean_value = mean(NUMERIC1)), by = "CHARACTER"]

#And now we play the plotting game (the plotting game is boring, lets
#play Hungry Hungry Hippos!)
plot <- ggplot(data, aes(CHARACTER, mean_value)) + geom_bar()

#And that should do it.

res <- aggregate(NUMERIC1 ~ GROUP, data = df, FUN = mean)
ggplot(res, aes(x = GROUP, y = NUMERIC1)) + geom_bar(stat = "identity")

数据 下面是一个使用dplyr创建摘要的解决方案。在这种情况下，摘要是在ggplot中动态创建的，但是您也可以先创建一个单独的摘要数据帧，然后将其提供给ggplot

由于绘制的是平均值，而不是计数，因此使用点而不是条形图可能更有意义。例如：

ggplot(df %>% group_by(GROUP) %>% 
         summarise(`Mean NUMERIC1`=mean(NUMERIC1)),
       aes(GROUP, `Mean NUMERIC1`)) + 
  geom_point(pch=21, size=5, fill="blue") + 
  coord_cartesian(ylim=c(0,310))

这就是统计结果玛丽。。。设计用于：

colnames(df) <- c("N1","N2","GROUP")
library(ggplot2)
ggplot(df) + stat_summary(aes(x=GROUP,y=N1),fun.y=mean,geom="bar", 
                          fill="lightblue",col="grey50")

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当您可以对自己的代码和条形图执行相同操作时，为什么要进行ggplot：

barplot(tapply(df$NUMERIC1, df$GROUP, FUN=mean))

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我已经安装并加载了ggplot2，但是当我尝试绘制绘图时，我可以看到：错误：找不到函数ggplot2，因为没有这样的函数。现在试试+1，关于统计摘要的观点很好！这就是生成条形图的ggplot2惯用方法。