[英]How to add percent of each category to stacked bar chart (ggplot2) (for a “non-percent” stacked chart)
How can I add the percent of each category to a stacked bar chart of the axis and not the fill. 如何将每个类别的百分比添加到堆积的轴条形图中,而不是填充中。 For example, I have the following dataset: 例如,我有以下数据集:
df<-structure(list(age_group = structure(c(3L, 3L, 5L, 3L, 5L, 5L,
5L, 3L, 5L, 5L, 4L, 4L, 4L, 3L, 5L), .Label = c("65+", "55-64",
"45-54", "35-44", "25-34", "18-24"), class = "factor"), Gender = c("F",
"M", "M", "M", "F", "M", "M", "M", "F", "M", "M", "F", "M", "F",
"M")), class = c("tbl_df", "tbl", "data.frame"), row.names = c(NA,
-15L), .Names = c("age_group", "Gender"))
dat <- aggregate(list(value = 1:NROW(df)), df[c("age_group", "Gender")], length)
dat$proportion <- ave(dat$value, dat$age_group, FUN = function(x) (x/sum(x)*100))
dat$proportionR <- round(dat$proportion, digits =0)
dat<-dat %>%
group_by(age_group) %>%
mutate(age_per = sum(value)) %>%
ungroup() %>%
mutate(age_per = round((age_per/sum(value))*100))
ggplot(dat, aes(x = age_group, y = value, fill = Gender)) +
geom_col() + coord_flip() + ylab("Visits 2018-2019") +xlab("") +
scale_fill_manual(values= c("#740404", "#AB6868", "#D5B3B3"), labels = c("Females", "Males", "N/A")) +
theme(legend.title=element_blank()) +
geom_text(aes(label = paste0(age_per, "%")), hjust = 2.7, position = "stack", color = "white", size =5)
What I would like is an automated way to add the total percent for each group from the y-axis while disregarding the percentages within each group. 我想要的是一种自动方法,可以从y轴添加每个组的总百分比 ,而忽略每个组中的百分比。 My work flow identifies the correct percent but replicates it over each subgroup within the stack. 我的工作流程确定了正确的百分比,但将其复制到堆栈中的每个子组上。 I would like the geom_text
to be placed in the white space right after bar ends. 我希望将geom_text
放在小节结束后的空白处。
Just as a note, the question is not a duplicate of the following SO Q - Adding percentage labels to a bar chart in ggplot2 -because this question deals with percents when there are stacked groups within each bar (the former is just for bar plots). 请注意,该问题不是以下SO Q的重复内容- 在ggplot2中向条形图中添加百分比标签 -因为当每个条中有堆叠组时,此问题处理的是百分比(前者仅用于条形图) 。
Also, emphasis on automated. 另外,强调自动化。 I can do the following but in my real data set I have many more age group intervals, which makes the below approach untenable. 我可以执行以下操作,但是在我的真实数据集中,我有更多的年龄段间隔,这使得以下方法难以成立。
ggplot(dat, aes(x = age_group, y = value, fill = Gender)) +
geom_col() + coord_flip() + ylab("Visits 2018-2019") +xlab("") +
scale_fill_manual(values= c("#740404", "#AB6868", "#D5B3B3"), labels = c("Females", "Males", "N/A")) +
theme(legend.title=element_blank()) +
geom_text(aes(y= 5.2, x=1, label = "33%"), color = "#740404", size =5) +
geom_text(aes(y= 3.2, x=2, label = "20%"), color = "#740404", size =5) +
geom_text(aes(y= 7.2, x=3, label = "47%"), color = "#740404", size =5)
Consider annotating using a grouping percent calculation. 考虑使用分组百分比计算进行注释。 Since you need to add three numbers with a series of six, annotate
can diverge from grouping series. 由于您需要将三个数字与六个序列相加,因此annotate
可以与分组序列有所不同。 Also, use the appropriate gender and age group percentages. 另外,使用适当的性别和年龄组百分比。 And below another base::ave
call replaces your dplyr::group_by
: 在另一个base::ave
调用下面替换您的dplyr::group_by
:
agg_df <- aggregate(list(value = 1:NROW(df)), df[c("age_group", "Gender")], length)
dat <- within(agg_df, {
proportion <- ave(value, age_group, FUN = function(x) (x/sum(x)*100))
proportionR <- round(proportion, digits=0)
age_per <- round((ave(value, age_group, Gender, FUN=sum) / sum(value)) * 100)
grp_pct <- round((ave(value, age_group, FUN=sum) / sum(value)) * 100)
})
dat
# age_group Gender value grp_pct age_per proportionR proportion
# 1 45-54 F 2 33 13 40 40.00000
# 2 35-44 F 1 20 7 33 33.33333
# 3 25-34 F 2 47 13 29 28.57143
# 4 45-54 M 3 33 20 60 60.00000
# 5 35-44 M 2 20 13 67 66.66667
# 6 25-34 M 5 47 33 71 71.42857
ggplot(dat, aes(x = age_group, y = value, fill = Gender)) +
geom_col() + coord_flip() + ylab("Visits 2018-2019") +xlab("") +
scale_fill_manual(values= c("#740404", "#AB6868", "#D5B3B3"),
labels = c("Females", "Males", "N/A")) +
theme(legend.title=element_blank()) +
geom_text(aes(label = paste0(age_per, "%")), hjust = 2.7,
position = "stack", color = "white", size =5) +
annotate("text", x=1, y=5.25, label = paste0(dat$grp_pct[[1]], "%")) +
annotate("text", x=2, y=3.25, label = paste0(dat$grp_pct[[2]], "%")) +
annotate("text", x=3, y=7.25, label = paste0(dat$grp_pct[[3]], "%"))
For dynamic annotating, you may have to use the functional form of ggplot
using Reduce
where the +
(not actually the plus arithmetic operator) is exposed as +.gg()
operator. 对于动态注释,您可能必须使用ggplot
Reduce
的ggplot
功能形式,其中+
(实际上不是加号算术运算符)被公开为+.gg()
运算符。 Then, call mapply
to iterate through unique(grp_pct)
to pass in x coordinate location and annotate label. 然后,调用mapply
以遍历unique(grp_pct)
以传递x坐标位置并注释标签。 Remaining challenge is that the best y coordinate is unknown. 剩下的挑战是最佳y坐标是未知的。
Reduce(ggplot2:::`+.gg`,
c(list(ggplot(dat, aes(x = age_group, y = value, fill = Gender)),
geom_col(), coord_flip(), ylab("Visits 2018-2019"), xlab(""),
scale_fill_manual(values= c("#740404", "#AB6868", "#D5B3B3"),
labels = c("Females", "Males", "N/A")),
theme(legend.title=element_blank()),
geom_text(aes(label = paste0(age_per, "%")), hjust = 2.7,
position = "stack", color = "white", size =5)
),
Map(function(x_loc, g_lab) annotate("text", x=x_loc, y=7.25,
label = paste0(g_lab, "%")),
seq(length(unique(dat$grp_pct))), unique(dat$grp_pct)
)
)
)
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