如何在 ggplot 中为数字 x 轴添加直接标签到条形图
How to add direct labels to a bar chart in ggplot for numeric x axis
我正在尝试在 ggplot 中创建一个条形图，其中条形的宽度与变量相关联 Cost$Sum.of.FS_P_Reduction_Kg。我正在使用参数 width=Sum.of.FS_P_Reduction_Kg 根据变量设置条形的宽度。
我想在图表中添加直接标签来标记每个条形，类似于下面记录的图像。我也在寻求添加与参数 width=Sum.of.FS_P_Reduction_Kg. 相对应的 x 轴标签。任何帮助将不胜感激。我知道 ggrepel 但到目前为止还没有达到预期的效果。
我使用了以下代码：
# Plot the data
P1 <- ggplot(Cost,
aes(x = Row.Labels,
y = Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost,
width = Average.of.FS_Annual_P_Reduction_Kg, label = Row.Labels)) +
geom_col(fill = "grey", colour = "black") +
geom_label_repel(
arrow = arrow(length = unit(0.03, "npc"), type = "closed", ends = "first"),
force = 10,
xlim = NA) +
facet_grid(~reorder(Row.Labels,
Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost),
scales = "free_x", space = "free_x") +
labs(x = "Measure code and average P reduction (kg/P/yr)",
y = "Mean annual TOTEX (£/kg) of P removal (thousands)") +
coord_cartesian(expand = FALSE) + # remove spacing within each facet
theme_classic() +
theme(strip.text = element_blank(), # hide facet title (since it's same as x label anyway)
panel.spacing = unit(0, "pt"), # remove spacing between facets
plot.margin = unit(c(rep(5.5, 3), 10), "pt"), # more space on left for axis label
axis.title=element_text(size=14),
axis.text.y = element_text(size=12),
axis.text.x = element_text(size=12, angle=45, vjust=0.2, hjust=0.1)) +
scale_x_discrete(labels = function(x) str_wrap(x, width = 10))
P1 = P1 + scale_y_continuous(labels = function(x) format(x/1000))
P1
示例数据 table 可以使用以下代码重现：
> dput(Cost)
structure(list(Row.Labels = structure(c(1L, 2L, 6L, 9L, 4L, 3L,
5L, 7L, 8L), .Label = c("Change the way P is applied", "Improve management of manure",
"In channel measures to slow flow", "Keep stock away from watercourses",
"No till trial ", "Reduce runoff from tracks and gateways", "Reversion to different vegetation",
"Using buffer strips to intercept pollutants", "Water features to intercept pollutants"
), class = "factor"), Average.of.FS_Annual_P_Reduction_Kg = c(0.11,
1.5425, 1.943, 3.560408144, 1.239230769, 18.49, 0.091238043,
1.117113762, 0.11033263), Average.of.FS_._Change = c(0.07, 0.975555556,
1.442, 1.071692763, 1.212307692, 8.82, 0.069972352, 0.545940711,
0.098636339), Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost = c(2792.929621,
2550.611429, 964.061346, 9966.056875, 2087.021801, 57.77580744,
165099.0425, 20682.62962, 97764.80805), Sum.of.Total_._Cost = c(358.33,
114310.49, 19508.2, 84655, 47154.23, 7072, 21210, 106780.34,
17757.89), Average.of.STW_Treatment_Cost_BASIC = c(155.1394461,
155.1394461, 155.1394461, 155.1394461, 155.1394461, 155.1394461,
155.1394461, 155.1394461, 155.1394461), Average.of.STW_Treatment_Cost_HIGH = c(236.4912345,
236.4912345, 236.4912345, 236.4912345, 236.4912345, 236.4912345,
236.4912345, 236.4912345, 236.4912345), Average.of.STW_Treatment_Cost_INTENSIVE = c(1023.192673,
1023.192673, 1023.192673, 1023.192673, 1023.192673, 1023.192673,
1023.192673, 1023.192673, 1023.192673)), class = "data.frame", row.names = c(NA,
-9L))
我认为做一些数据准备会更容易，这样您就可以将所有框放在一个具有共享 x 轴的平面上。例如，我们可以计算减少Kg的累积和，并用它来定义每个盒子的起始x。
编辑 -- 添加 ylim = c(0, NA), xlim = c(0, NA), 以将 ggrepel::geom_text_repel 文本保持在绘图的正范围内。
library(ggplot2)
library(ggrepel)
library(stringr)
library(dplyr)
Cost %>%
arrange(desc(Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost)) %>%
mutate(Row.Labels = forcats::fct_inorder(Row.Labels),
cuml_reduc = cumsum(Average.of.FS_Annual_P_Reduction_Kg),
bar_start = cuml_reduc - Average.of.FS_Annual_P_Reduction_Kg,
bar_center = cuml_reduc - 0.5*Average.of.FS_Annual_P_Reduction_Kg) %>%
ggplot(aes(xmin = bar_start, xmax = cuml_reduc,
ymin = 0, ymax = Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost)) +
geom_rect(fill = "grey", colour = "black") +
geom_text_repel(aes(x = bar_center,
y = Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost,
label = str_wrap(Row.Labels, 15)),
ylim = c(0, NA), xlim = c(0, NA), ## EDIT
size = 3, nudge_y = 1E4, nudge_x = 2, lineheight = 0.7,
segment.alpha = 0.3) +
scale_y_continuous(labels = scales::comma) +
labs(x = "Measure code and average P reduction (kg/P/yr)",
y = "Mean annual TOTEX (£/kg) of P removal (thousands)")
您可以尝试稍微缩放值，例如使用对数化。因为我更喜欢 baseplots 而不是 gglplot2 我会相应地使用 barplot 向您展示一个基本解决方案。
首先，我们将第一列转换为行名并将其删除。
cost <- `rownames<-`(Cost[-1], Cost[,1])
在 barplot 中定义宽度非常简单，因为它有一个选项 width=，我们可以在其中输入相应变量的对数值。对于条形标签，我们需要计算位置并使用 text；为了实现换行，我们可以使用 strwrap。如果是困难情况，可以方便地省略标签（如示例中的#6）。最后我们使用（无头）arrows .
# logarithmize values
w <- log(w1 <- cost$Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost)
# define vector labels inside / outside, at best by hand
inside <- as.logical(c(0, 1, 0, 1, 1, 0, 1, 1, 1))
# calculate `x0` values of labels
x0 <- w / 2 + c(0, cumsum(w)[- length(w)])
# define y values o. labels
y0 <- ifelse(inside, colSums(t(cost)) / 2, 1.5e5)
# make labels using 'strwrap'
labs <- mapply(paste, strwrap(rownames(cost), 15, simplify=F), collapse="\n")
# define nine colors
colores <- hcl.colors(9, "Spectral", alpha=.7)
# the actual plot
b <- barplot(cs <- colSums(t(cost)), width=w, space=0, ylim=c(1, 2e5),
xlim=c(-1, 80), xaxt="n", xaxs="i", col=colores, border=NA,
xlab="Measure code and average P reduction (kg/P/yr)",
ylab="Mean annual TOTEX (£/kg) of P removal (thousands)")
# place lables, leave out # 6
text(x0[-6], y0[-6], labels=labs[-6], cex=.7)
# arrows
arrows(x0[c(1, 3)], 1.35e5, x0[c(1, 3)], cs[c(1, 3)], length=0)
# label # 6
text(40, 1e5, labs[6], cex=.7)
# arrow # 6
arrows(40, 8.4e4, x0[6], cs[6], length=0)
# make x axis
axis(1, c(0, cumsum(log(seq(0, 1e5, 1e4)[-1]))),
labels=format(c(0, cumsum(seq(0, 1e5, 1e4)[-1])), format="d"), tck=-.02)
# put it in a box
box()
结果
我希望我得到正确的 x 轴值。
您可能需要了解一些可能的新功能是如何工作的，但是使用帮助文件非常容易，例如输入 ?barplot.
我正在尝试在 ggplot 中创建一个条形图，其中条形的宽度与变量相关联 Cost$Sum.of.FS_P_Reduction_Kg。我正在使用参数 width=Sum.of.FS_P_Reduction_Kg 根据变量设置条形的宽度。
我想在图表中添加直接标签来标记每个条形，类似于下面记录的图像。我也在寻求添加与参数 width=Sum.of.FS_P_Reduction_Kg. 相对应的 x 轴标签。任何帮助将不胜感激。我知道 ggrepel 但到目前为止还没有达到预期的效果。
我使用了以下代码：
# Plot the data
P1 <- ggplot(Cost,
aes(x = Row.Labels,
y = Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost,
width = Average.of.FS_Annual_P_Reduction_Kg, label = Row.Labels)) +
geom_col(fill = "grey", colour = "black") +
geom_label_repel(
arrow = arrow(length = unit(0.03, "npc"), type = "closed", ends = "first"),
force = 10,
xlim = NA) +
facet_grid(~reorder(Row.Labels,
Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost),
scales = "free_x", space = "free_x") +
labs(x = "Measure code and average P reduction (kg/P/yr)",
y = "Mean annual TOTEX (£/kg) of P removal (thousands)") +
coord_cartesian(expand = FALSE) + # remove spacing within each facet
theme_classic() +
theme(strip.text = element_blank(), # hide facet title (since it's same as x label anyway)
panel.spacing = unit(0, "pt"), # remove spacing between facets
plot.margin = unit(c(rep(5.5, 3), 10), "pt"), # more space on left for axis label
axis.title=element_text(size=14),
axis.text.y = element_text(size=12),
axis.text.x = element_text(size=12, angle=45, vjust=0.2, hjust=0.1)) +
scale_x_discrete(labels = function(x) str_wrap(x, width = 10))
P1 = P1 + scale_y_continuous(labels = function(x) format(x/1000))
P1
示例数据 table 可以使用以下代码重现：
> dput(Cost)
structure(list(Row.Labels = structure(c(1L, 2L, 6L, 9L, 4L, 3L,
5L, 7L, 8L), .Label = c("Change the way P is applied", "Improve management of manure",
"In channel measures to slow flow", "Keep stock away from watercourses",
"No till trial ", "Reduce runoff from tracks and gateways", "Reversion to different vegetation",
"Using buffer strips to intercept pollutants", "Water features to intercept pollutants"
), class = "factor"), Average.of.FS_Annual_P_Reduction_Kg = c(0.11,
1.5425, 1.943, 3.560408144, 1.239230769, 18.49, 0.091238043,
1.117113762, 0.11033263), Average.of.FS_._Change = c(0.07, 0.975555556,
1.442, 1.071692763, 1.212307692, 8.82, 0.069972352, 0.545940711,
0.098636339), Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost = c(2792.929621,
2550.611429, 964.061346, 9966.056875, 2087.021801, 57.77580744,
165099.0425, 20682.62962, 97764.80805), Sum.of.Total_._Cost = c(358.33,
114310.49, 19508.2, 84655, 47154.23, 7072, 21210, 106780.34,
17757.89), Average.of.STW_Treatment_Cost_BASIC = c(155.1394461,
155.1394461, 155.1394461, 155.1394461, 155.1394461, 155.1394461,
155.1394461, 155.1394461, 155.1394461), Average.of.STW_Treatment_Cost_HIGH = c(236.4912345,
236.4912345, 236.4912345, 236.4912345, 236.4912345, 236.4912345,
236.4912345, 236.4912345, 236.4912345), Average.of.STW_Treatment_Cost_INTENSIVE = c(1023.192673,
1023.192673, 1023.192673, 1023.192673, 1023.192673, 1023.192673,
1023.192673, 1023.192673, 1023.192673)), class = "data.frame", row.names = c(NA,
-9L))
我认为做一些数据准备会更容易，这样您就可以将所有框放在一个具有共享 x 轴的平面上。例如，我们可以计算减少Kg的累积和，并用它来定义每个盒子的起始x。
编辑 -- 添加 ylim = c(0, NA), xlim = c(0, NA), 以将 ggrepel::geom_text_repel 文本保持在绘图的正范围内。
library(ggplot2)
library(ggrepel)
library(stringr)
library(dplyr)
Cost %>%
arrange(desc(Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost)) %>%
mutate(Row.Labels = forcats::fct_inorder(Row.Labels),
cuml_reduc = cumsum(Average.of.FS_Annual_P_Reduction_Kg),
bar_start = cuml_reduc - Average.of.FS_Annual_P_Reduction_Kg,
bar_center = cuml_reduc - 0.5*Average.of.FS_Annual_P_Reduction_Kg) %>%
ggplot(aes(xmin = bar_start, xmax = cuml_reduc,
ymin = 0, ymax = Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost)) +
geom_rect(fill = "grey", colour = "black") +
geom_text_repel(aes(x = bar_center,
y = Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost,
label = str_wrap(Row.Labels, 15)),
ylim = c(0, NA), xlim = c(0, NA), ## EDIT
size = 3, nudge_y = 1E4, nudge_x = 2, lineheight = 0.7,
segment.alpha = 0.3) +
scale_y_continuous(labels = scales::comma) +
labs(x = "Measure code and average P reduction (kg/P/yr)",
y = "Mean annual TOTEX (£/kg) of P removal (thousands)")
您可以尝试稍微缩放值，例如使用对数化。因为我更喜欢 baseplots 而不是 gglplot2 我会相应地使用 barplot 向您展示一个基本解决方案。
首先，我们将第一列转换为行名并将其删除。
cost <- `rownames<-`(Cost[-1], Cost[,1])
在 barplot 中定义宽度非常简单，因为它有一个选项 width=，我们可以在其中输入相应变量的对数值。对于条形标签，我们需要计算位置并使用 text；为了实现换行，我们可以使用 strwrap。如果是困难情况，可以方便地省略标签（如示例中的#6）。最后我们使用（无头）arrows .
# logarithmize values
w <- log(w1 <- cost$Average.of.Cost_Per_Kg_P_Removal.undiscounted..LOW_Oncost)
# define vector labels inside / outside, at best by hand
inside <- as.logical(c(0, 1, 0, 1, 1, 0, 1, 1, 1))
# calculate `x0` values of labels
x0 <- w / 2 + c(0, cumsum(w)[- length(w)])
# define y values o. labels
y0 <- ifelse(inside, colSums(t(cost)) / 2, 1.5e5)
# make labels using 'strwrap'
labs <- mapply(paste, strwrap(rownames(cost), 15, simplify=F), collapse="\n")
# define nine colors
colores <- hcl.colors(9, "Spectral", alpha=.7)
# the actual plot
b <- barplot(cs <- colSums(t(cost)), width=w, space=0, ylim=c(1, 2e5),
xlim=c(-1, 80), xaxt="n", xaxs="i", col=colores, border=NA,
xlab="Measure code and average P reduction (kg/P/yr)",
ylab="Mean annual TOTEX (£/kg) of P removal (thousands)")
# place lables, leave out # 6
text(x0[-6], y0[-6], labels=labs[-6], cex=.7)
# arrows
arrows(x0[c(1, 3)], 1.35e5, x0[c(1, 3)], cs[c(1, 3)], length=0)
# label # 6
text(40, 1e5, labs[6], cex=.7)
# arrow # 6
arrows(40, 8.4e4, x0[6], cs[6], length=0)
# make x axis
axis(1, c(0, cumsum(log(seq(0, 1e5, 1e4)[-1]))),
labels=format(c(0, cumsum(seq(0, 1e5, 1e4)[-1])), format="d"), tck=-.02)
# put it in a box
box()
结果
我希望我得到正确的 x 轴值。
您可能需要了解一些可能的新功能是如何工作的，但是使用帮助文件非常容易，例如输入 ?barplot.