如何在R中创建“堆积瀑布图”图表？ [英] How to create a 'stacked waterfall' chart in R?
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问题描述
我能够找到几个在R中创建瀑布图的软件包，如下所示：
但是我无法找到创建如下所示的堆积瀑布图的方法：
I was able to find several packages to create a waterfall chart in R which look like this: But I could not find a way to create a stacked waterfall charts which look like this:
一个解决方法是使用堆叠的条形图。但这不是一个优雅的方法。因此，我想知道是否有更好的方法可以在R中创建堆叠式瀑布图。
A work around is to use stacked bar chart. But that is not an elegant way. So, I wanted to know if there is a better way to create stacked waterfall chart in R.
推荐答案
您可以轻松创建拥有正确数据后，使用 ggplot2 进行主绘制。使用颜色，文本，线条等选择来复制所需的图，需要做更多的工作，但可行。
You can easily create the "main" plot with ggplot2 once you have the "right" data. To replicate the plot you want with the choices of color, text, lines, etc., takes more work, but is doable.
使用 ggplot2 绘制瀑布图的技巧是用组（x值-I在我的代码中以您要绘制的确切顺序将其称为 x.axis.Var ）。之后，您需要获取组中每个类别（图例中的类别- cat.Var ）的小节的起点和终点。然后，您创建另一个具有类别总数的组。您还需要一个数字索引来对各组进行操作。最后，获得一栏，其中按组总计表示条形上方的数字。
The trick to plot waterfall charts with ggplot2 is to create a data set with the groups (x values - I'm calling this in my code as x.axis.Var) in the exact order you want to plot. After that, you need to get the start and end points of the bars for each category (categories in your legend - cat.Var) within the groups. Then, you create another group with the totals by category. You'll also need a numeric index for the groups to manipulate the bars. Finally, get a column with the total by group for the numbers above the bars.
假设您的数据框如下所示：
Suppose your data frame looks like this:
df <-
data.frame(
x.axis.Var = rep(c("Widgets", "Gridgets", "Groms", "Wobs"), 3),
cat.Var = rep(c("High End", "Mid Range", "Low End"), each = 4),
values = c(600, 500, 300, 200, # high end
300, 200, 300, 250, # mid range
100, 80, 200, 150 # low end
)
)
或者，
x.axis.Var cat.Var values
1 Widgets High End 600
2 Gridgets High End 500
3 Groms High End 300
4 Wobs High End 200
5 Widgets Mid Range 300
6 Gridgets Mid Range 200
7 Groms Mid Range 300
8 Wobs Mid Range 250
9 Widgets Low End 100
10 Gridgets Low End 80
11 Groms Low End 200
12 Wobs Low End 150
按照上面的步骤获得新数据框：
Follow the steps above to get a new data frame:
df.tmp <- df %>%
# \_Set the factor levels in the order you want ----
mutate(
x.axis.Var = factor(x.axis.Var,
levels = c("Widgets", "Gridgets", "Groms", "Wobs")),
cat.Var = factor(cat.Var,
levels = c("Low End", "Mid Range", "High End"))
) %>%
# \_Sort by Group and Category ----
arrange(x.axis.Var, desc(cat.Var)) %>%
# \_Get the start and end points of the bars ----
mutate(end.Bar = cumsum(values),
start.Bar = c(0, head(end.Bar, -1))) %>%
# \_Add a new Group called 'Total' with total by category ----
rbind(
df %>%
# \___Sum by Categories ----
group_by(cat.Var) %>%
summarise(values = sum(values)) %>%
# \___Create new Group: 'Total' ----
mutate(
x.axis.Var = "Total",
cat.Var = factor(cat.Var,
levels = c("Low End", "Mid Range", "High End"))
) %>%
# \___Sort by Group and Category ----
arrange(x.axis.Var, desc(cat.Var)) %>%
# \___Get the start and end points of the bars ----
mutate(end.Bar = cumsum(values),
start.Bar = c(0, head(end.Bar, -1))) %>%
# \___Put variables in the same order ----
select(names(df),end.Bar,start.Bar)
) %>%
# \_Get numeric index for the groups ----
mutate(group.id = group_indices(., x.axis.Var)) %>%
# \_Create new variable with total by group ----
group_by(x.axis.Var) %>%
mutate(total.by.x = sum(values)) %>%
# \_Order the columns ----
select(x.axis.Var, cat.Var, group.id, start.Bar, values, end.Bar, total.by.x)
结果如下：
x.axis.Var cat.Var group.id start.Bar values end.Bar total.by.x
<fct> <fct> <int> <dbl> <dbl> <dbl> <dbl>
1 Widgets High End 1 0 600 600 1000
2 Widgets Mid Range 1 600 300 900 1000
3 Widgets Low End 1 900 100 1000 1000
4 Gridgets High End 2 1000 500 1500 780
5 Gridgets Mid Range 2 1500 200 1700 780
6 Gridgets Low End 2 1700 80 1780 780
7 Groms High End 3 1780 300 2080 800
8 Groms Mid Range 3 2080 300 2380 800
9 Groms Low End 3 2380 200 2580 800
10 Wobs High End 4 2580 200 2780 600
11 Wobs Mid Range 4 2780 250 3030 600
12 Wobs Low End 4 3030 150 3180 600
13 Total High End 5 0 1600 1600 3180
14 Total Mid Range 5 1600 1050 2650 3180
15 Total Low End 5 2650 530 3180 3180
然后，我们可以使用 geom_rect 创建主图：
Then, we can use geom_rect to create the "main" plot:
ggplot(df.tmp, aes( x = x.axis.Var, fill = cat.Var)) +
# Waterfall Chart
geom_rect(aes(x = x.axis.Var,
xmin = group.id - 0.25, # control bar gap width
xmax = group.id + 0.25,
ymin = end.Bar,
ymax = start.Bar)
)
并获得：
And get:
因此，组和类别的顺序是正确的。要将瀑布图绘制为原始图，我将对上面的代码进行一次更改。我将使用 x = group.id 而不是使用 x = x.axis.Var 我对刻度线进行所需的更改。进行此更改并进行设计更改的代码为：
So, the order of the groups and categories is correct. To plot the waterfall chart as the original one I'll make one change to the code above. Instead of using x = x.axis.Var, I'll use x = group.id because this will allow me to make the desired changes to the tick marks. The code with this change and with the design changes is:
ggplot(df.tmp, aes(x = group.id, fill = cat.Var)) +
# \_Simple Waterfall Chart ----
geom_rect(aes(x = group.id,
xmin = group.id - 0.25, # control bar gap width
xmax = group.id + 0.25,
ymin = end.Bar,
ymax = start.Bar),
color="black",
alpha=0.95) +
# \_Lines Between Bars ----
geom_segment(aes(x=ifelse(group.id == last(group.id),
last(group.id),
group.id+0.25),
xend=ifelse(group.id == last(group.id),
last(group.id),
group.id+0.75),
y=ifelse(cat.Var == "Low End",
end.Bar,
# these will be removed once we set the y limits
max(end.Bar)*2),
yend=ifelse(cat.Var == "Low End",
end.Bar,
# these will be removed once we set the y limits
max(end.Bar)*2)),
colour="black") +
# \_Numbers inside bars (each category) ----
geom_text(
mapping =
aes(
label = ifelse(values < 150,
"",
ifelse(nchar(values) == 3,
as.character(values),
sub("(.{1})(.*)", "\\1.\\2",
as.character(values)
)
)
),
y = rowSums(cbind(start.Bar,values/2))
),
color = "white",
fontface = "bold"
) +
# \_Total for each category above bars ----
geom_text(
mapping =
aes(
label = ifelse(cat.Var != "Low End",
"",
ifelse(nchar(total.by.x) == 3,
as.character(total.by.x),
sub("(.{1})(.*)", "\\1.\\2",
as.character(total.by.x)
)
)
),
y = end.Bar+200
),
color = "#4e4d47",
fontface = "bold"
) +
# \_Change colors ----
scale_fill_manual(values=c('#c8f464','#ff6969','#55646e')) +
# \_Change y axis to same scale as original ----
scale_y_continuous(
expand=c(0,0),
limits = c(0, 3500),
breaks = seq(0, 3500, 500),
labels = ifelse(nchar(seq(0, 3500, 500)) < 4,
as.character(seq(0, 3500, 500)),
sub("(.{1})(.*)", "\\1.\\2",
as.character(seq(0, 3500, 500))
)
)
) +
# \_Add tick marks on x axis to look like the original plot ----
scale_x_continuous(
expand=c(0,0),
limits = c(min(df.tmp$group.id)-0.5,max(df.tmp$group.id)+0.5),
breaks = c(min(df.tmp$group.id)-0.5,
unique(df.tmp$group.id),
unique(df.tmp$group.id) + 0.5
),
labels =
c("",
as.character(unique(df.tmp$x.axis.Var)),
rep(c(""), length(unique(df.tmp$x.axis.Var)))
)
) +
# \_Theme options to make it look like the original plot ----
theme(
text = element_text(size = 14, color = "#4e4d47"),
axis.text = element_text(size = 10, color = "#4e4d47", face = "bold"),
axis.text.y = element_text(margin = margin(r = 0.3, unit = "cm")),
axis.ticks.x =
element_line(color =
c("black",
rep(NA, length(unique(df.tmp$x.axis.Var))),
rep("black", length(unique(df.tmp$x.axis.Var))-1)
)
),
axis.line = element_line(colour = "#4e4d47", size = 0.5),
axis.ticks.length = unit(.15, "cm"),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.background = element_blank(),
plot.margin = unit(c(1, 1, 1, 1), "lines"),
legend.text = element_text(size = 10,
color = "#4e4d47",
face = "bold",
margin = margin(l = 0.25, unit = "cm")
),
legend.title = element_blank()
)
最后一个图：
And the final plot:
# ************************************************************************* ----
# Packages ----
# ************************************************************************* ----
library("ggplot2")
library("dplyr")
# ************************************************************************* ----
# Original data ----
# ************************************************************************* ----
df <-
data.frame(
x.axis.Var = rep(c("Widgets", "Gridgets", "Groms", "Wobs"), 3),
cat.Var = rep(c("High End", "Mid Range", "Low End"), each = 4),
values = c(600, 500, 300, 200, # high end
300, 200, 300, 250, # mid range
100, 80, 200, 150 # low end
)
)
# ************************************************************************* ----
# Data for Waterfall Chart ----
# ************************************************************************* ----
df.tmp <- df %>%
# \_Set the factor levels in the order you want ----
mutate(
x.axis.Var = factor(x.axis.Var,
levels = c("Widgets", "Gridgets", "Groms", "Wobs")),
cat.Var = factor(cat.Var,
levels = c("Low End", "Mid Range", "High End"))
) %>%
# \_Sort by Group and Category ----
arrange(x.axis.Var, desc(cat.Var)) %>%
# \_Get the start and end points of the bars ----
mutate(end.Bar = cumsum(values),
start.Bar = c(0, head(end.Bar, -1))) %>%
# \_Add a new Group called 'Total' with total by category ----
rbind(
df %>%
# \___Sum by Categories ----
group_by(cat.Var) %>%
summarise(values = sum(values)) %>%
# \___Create new Group: 'Total' ----
mutate(
x.axis.Var = "Total",
cat.Var = factor(cat.Var,
levels = c("Low End", "Mid Range", "High End"))
) %>%
# \___Sort by Group and Category ----
arrange(x.axis.Var, desc(cat.Var)) %>%
# \___Get the start and end points of the bars ----
mutate(end.Bar = cumsum(values),
start.Bar = c(0, head(end.Bar, -1))) %>%
# \___Put variables in the same order ----
select(names(df),end.Bar,start.Bar)
) %>%
# \_Get numeric index for the groups ----
mutate(group.id = group_indices(., x.axis.Var)) %>%
# \_Create new variable with total by group ----
group_by(x.axis.Var) %>%
mutate(total.by.x = sum(values)) %>%
# \_Order the columns ----
select(x.axis.Var, cat.Var, group.id, start.Bar, values, end.Bar, total.by.x)
# ************************************************************************* ----
# Plot ----
# ************************************************************************* ----
ggplot(df.tmp, aes(x = group.id, fill = cat.Var)) +
# \_Simple Waterfall Chart ----
geom_rect(aes(x = group.id,
xmin = group.id - 0.25, # control bar gap width
xmax = group.id + 0.25,
ymin = end.Bar,
ymax = start.Bar),
color="black",
alpha=0.95) +
# \_Lines Between Bars ----
geom_segment(aes(x=ifelse(group.id == last(group.id),
last(group.id),
group.id+0.25),
xend=ifelse(group.id == last(group.id),
last(group.id),
group.id+0.75),
y=ifelse(cat.Var == "Low End",
end.Bar,
# these will be removed once we set the y limits
max(end.Bar)*2),
yend=ifelse(cat.Var == "Low End",
end.Bar,
# these will be removed once we set the y limits
max(end.Bar)*2)),
colour="black") +
# \_Numbers inside bars (each category) ----
geom_text(
mapping =
aes(
label = ifelse(values < 150,
"",
ifelse(nchar(values) == 3,
as.character(values),
sub("(.{1})(.*)", "\\1.\\2",
as.character(values)
)
)
),
y = rowSums(cbind(start.Bar,values/2))
),
color = "white",
fontface = "bold"
) +
# \_Total for each category above bars ----
geom_text(
mapping =
aes(
label = ifelse(cat.Var != "Low End",
"",
ifelse(nchar(total.by.x) == 3,
as.character(total.by.x),
sub("(.{1})(.*)", "\\1.\\2",
as.character(total.by.x)
)
)
),
y = end.Bar+200
),
color = "#4e4d47",
fontface = "bold"
) +
# \_Change colors ----
scale_fill_manual(values=c('#c8f464','#ff6969','#55646e')) +
# \_Change y axis to same scale as original ----
scale_y_continuous(
expand=c(0,0),
limits = c(0, 3500),
breaks = seq(0, 3500, 500),
labels = ifelse(nchar(seq(0, 3500, 500)) < 4,
as.character(seq(0, 3500, 500)),
sub("(.{1})(.*)", "\\1.\\2",
as.character(seq(0, 3500, 500))
)
)
) +
# \_Add tick marks on x axis to look like the original plot ----
scale_x_continuous(
expand=c(0,0),
limits = c(min(df.tmp$group.id)-0.5,max(df.tmp$group.id)+0.5),
breaks = c(min(df.tmp$group.id)-0.5,
unique(df.tmp$group.id),
unique(df.tmp$group.id) + 0.5
),
labels =
c("",
as.character(unique(df.tmp$x.axis.Var)),
rep(c(""), length(unique(df.tmp$x.axis.Var)))
)
) +
# \_Theme options to make it look like the original plot ----
theme(
text = element_text(size = 14, color = "#4e4d47"),
axis.text = element_text(size = 10, color = "#4e4d47", face = "bold"),
axis.text.y = element_text(margin = margin(r = 0.3, unit = "cm")),
axis.ticks.x =
element_line(color =
c("black",
rep(NA, length(unique(df.tmp$x.axis.Var))),
rep("black", length(unique(df.tmp$x.axis.Var))-1)
)
),
axis.line = element_line(colour = "#4e4d47", size = 0.5),
axis.ticks.length = unit(.15, "cm"),
axis.title.x = element_blank(),
axis.title.y = element_blank(),
panel.background = element_blank(),
plot.margin = unit(c(1, 1, 1, 1), "lines"),
legend.text = element_text(size = 10,
color = "#4e4d47",
face = "bold",
margin = margin(l = 0.25, unit = "cm")
),
legend.title = element_blank()
)
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