War*_*ght 3 r bar-chart ggplot2 direct-labels ggrepel
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。我正在使用该参数width=Sum.of.FS_P_Reduction_Kg根据变量设置条形的宽度。
我想向图表添加直接标签以标记每个条形,类似于下面记录的图像。我也在寻求添加与参数相对应的 x 轴标签width=Sum.of.FS_P_Reduction_Kg.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
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示例数据表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))
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我认为做一些数据准备会更容易,这样你就可以把所有的盒子放在一个共享 x 轴的平面上。例如,我们可以计算减少 Kg 的累积总和,并使用它来定义每个框的起始 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)")
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