R中ggplot2中標簽文本的定位
[英]Positioning of label text in ggplot2 in R
問題描述
我正在使用geom_smooth制作折線圖並使用geom_smooth對其進行geom_dl 。 這些線還具有geom_points作為附加顯示。 文本位於點上，我希望文本位於平滑線的尾部。 我的代碼如下。
library(ggplot2)
library(directlabels)
ggplot(gedu5, aes(x = Year, y = gedu, colour = Country, group = Country)) +
geom_smooth(method = "lm", formula = y ~ poly(x, 3), se = FALSE)+
geom_point(stat = "identity") +
scale_colour_discrete(guide = 'none') +
geom_dl(aes(label = Country), method = list(dl.combine("first.points", "last.points"), cex = 1)) +
labs(title = "Government expenditure on education, total (% of GDP)", cex.main = 2.5) +
theme(axis.title = element_blank()) +
facet_wrap(.~Region, 2, scales="free")
它呈現的圖像如下所示。 正如你在圖片中看到的 標簽實際上是固定在點上而不是線上。 我想將標簽貼在線條上而不是點上。
上圖的數據在這里：
structure(list(Year = c(1998L, 1999L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 2016L, 2017L, 1998L, 1999L, 2000L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 1998L, 1999L,
2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L,
2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L,
1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L,
2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L,
2016L, 2017L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 1998L, 1999L, 2000L, 2001L, 2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 1998L, 1999L, 2000L,
2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L,
2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 1998L,
1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L,
2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L,
2017L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L,
2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L,
2015L, 2016L, 2017L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L,
2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L,
2013L, 2014L, 2015L, 2016L, 2017L, 1998L, 1999L, 2000L, 2001L,
2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L,
2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 1998L, 1999L,
2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L,
2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L,
1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L,
2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L,
2016L, 2017L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L,
2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L,
2014L, 2015L, 2016L, 2017L, 1998L, 1999L, 2000L, 2001L, 2002L,
2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L, 2010L, 2011L,
2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 1998L, 1999L, 2000L,
2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L, 2008L, 2009L,
2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L, 2017L, 1998L,
1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L, 2006L, 2007L,
2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L, 2015L, 2016L,
2017L, 1998L, 1999L, 2000L, 2001L, 2002L, 2003L, 2004L, 2005L,
2006L, 2007L, 2008L, 2009L, 2010L, 2011L, 2012L, 2013L, 2014L,
2015L, 2016L, 2017L), Country = c("Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan", "Afghanistan",
"Afghanistan", "Afghanistan", "Afghanistan", "Bangladesh", "Bangladesh",
"Bangladesh", "Bangladesh", "Bangladesh", "Bangladesh", "Bangladesh",
"Bangladesh", "Bangladesh", "Bangladesh", "Bangladesh", "Bangladesh",
"Bangladesh", "Bangladesh", "Bangladesh", "Bangladesh", "Bangladesh",
"Bangladesh", "Bangladesh", "Bangladesh", "Bhutan", "Bhutan",
"Bhutan", "Bhutan", "Bhutan", "Bhutan", "Bhutan", "Bhutan", "Bhutan",
"Bhutan", "Bhutan", "Bhutan", "Bhutan", "Bhutan", "Bhutan", "Bhutan",
"Bhutan", "Bhutan", "Bhutan", "Bhutan", "India", "India", "India",
"India", "India", "India", "India", "India", "India", "India",
"India", "India", "India", "India", "India", "India", "India",
"India", "India", "India", "Maldives", "Maldives", "Maldives",
"Maldives", "Maldives", "Maldives", "Maldives", "Maldives", "Maldives",
"Maldives", "Maldives", "Maldives", "Maldives", "Maldives", "Maldives",
"Maldives", "Maldives", "Maldives", "Maldives", "Maldives", "Nepal",
"Nepal", "Nepal", "Nepal", "Nepal", "Nepal", "Nepal", "Nepal",
"Nepal", "Nepal", "Nepal", "Nepal", "Nepal", "Nepal", "Nepal",
"Nepal", "Nepal", "Nepal", "Nepal", "Nepal", "Pakistan", "Pakistan",
"Pakistan", "Pakistan", "Pakistan", "Pakistan", "Pakistan", "Pakistan",
"Pakistan", "Pakistan", "Pakistan", "Pakistan", "Pakistan", "Pakistan",
"Pakistan", "Pakistan", "Pakistan", "Pakistan", "Pakistan", "Pakistan",
"Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka",
"Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka",
"Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka",
"Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka", "Sri_Lanka",
"World", "World", "World", "World", "World", "World", "World",
"World", "World", "World", "World", "World", "World", "World",
"World", "World", "World", "World", "World", "World", "South_Asia",
"South_Asia", "South_Asia", "South_Asia", "South_Asia", "South_Asia",
"South_Asia", "South_Asia", "South_Asia", "South_Asia", "South_Asia",
"South_Asia", "South_Asia", "South_Asia", "South_Asia", "South_Asia",
"South_Asia", "South_Asia", "South_Asia", "South_Asia", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Sub.Saharan_Africa", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Sub.Saharan_Africa", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Sub.Saharan_Africa", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Sub.Saharan_Africa", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Sub.Saharan_Africa", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Sub.Saharan_Africa", "Sub.Saharan_Africa",
"Sub.Saharan_Africa", "Middle_income", "Middle_income", "Middle_income",
"Middle_income", "Middle_income", "Middle_income", "Middle_income",
"Middle_income", "Middle_income", "Middle_income", "Middle_income",
"Middle_income", "Middle_income", "Middle_income", "Middle_income",
"Middle_income", "Middle_income", "Middle_income", "Middle_income",
"Middle_income", "Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Central_Europe_and_the_Baltics", "Central_Europe_and_the_Baltics",
"Euro_area", "Euro_area", "Euro_area", "Euro_area", "Euro_area",
"Euro_area", "Euro_area", "Euro_area", "Euro_area", "Euro_area",
"Euro_area", "Euro_area", "Euro_area", "Euro_area", "Euro_area",
"Euro_area", "Euro_area", "Euro_area", "Euro_area", "Euro_area",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Middle_East_North_Africa",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Middle_East_North_Africa",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Middle_East_North_Africa",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Middle_East_North_Africa",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Middle_East_North_Africa",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Middle_East_North_Africa",
"Middle_East_North_Africa", "Middle_East_North_Africa", "Latin_America_Caribbean",
"Latin_America_Caribbean", "Latin_America_Caribbean", "Latin_America_Caribbean",
"Latin_America_Caribbean", "Latin_America_Caribbean", "Latin_America_Caribbean",
"Latin_America_Caribbean", "Latin_America_Caribbean", "Latin_America_Caribbean",
"Latin_America_Caribbean", "Latin_America_Caribbean", "Latin_America_Caribbean",
"Latin_America_Caribbean", "Latin_America_Caribbean", "Latin_America_Caribbean",
"Latin_America_Caribbean", "Latin_America_Caribbean", "Latin_America_Caribbean",
"Latin_America_Caribbean", "North_America", "North_America",
"North_America", "North_America", "North_America", "North_America",
"North_America", "North_America", "North_America", "North_America",
"North_America", "North_America", "North_America", "North_America",
"North_America", "North_America", "North_America", "North_America",
"North_America", "North_America", "Low_income", "Low_income",
"Low_income", "Low_income", "Low_income", "Low_income", "Low_income",
"Low_income", "Low_income", "Low_income", "Low_income", "Low_income",
"Low_income", "Low_income", "Low_income", "Low_income", "Low_income",
"Low_income", "Low_income", "Low_income"), gedu = c(3.5, 3.8,
3.7, 3.3, 2.9, 2.6, 2.7, 3, 3.4, 3.7, 3.8, 3.7, 3.5, 3.5, 2.6,
3.5, 3.7, 3.3, 4.2, 4.1, 2.1, 2.1, 2.1, 2.2, 2, 2.1, 1.9, 2.1,
2.1, 2.2, 2, 1.9, 2, 2.1, 2.2, 2, 1.5, 1.3, 1.5, 2.5, 5.5, 5.7,
5.5, 5.7, 6.2, 6.8, 6.4, 7.1, 5.4, 4.8, 4.8, 4.6, 4, 4.7, 5.5,
5.6, 5.9, 7.3, 6.8, 7, 3.6, 4.4, 4.3, 4.2, 4, 3.6, 3.4, 3.2,
3.1, 3.2, 3.1, 3.3, 3.4, 3.8, 3.9, 3.8, 3.7, 3.9, 3.9, 3.8, 5.8,
5.5, 4.9, 4.7, 5.8, 5.3, 4.7, 5, 4.7, 4.4, 4.5, 5.8, 4.1, 3.5,
3.8, 3.8, 3.5, 4.4, 4.1, 4.1, 2.9, 2.9, 3, 3.7, 3.1, 3.1, 3.2,
3.4, 3.6, 3.5, 3.8, 4.7, 3.6, 3.8, 3.8, 3.5, 4, 3.7, 4.4, 5.5,
2.6, 2.6, 1.8, 1.5, 1.6, 1.9, 2, 2.2, 2.6, 2.6, 2.8, 2.6, 2.3,
2.2, 2.1, 2.5, 2.5, 2.6, 3, 2.9, 3, 5.2, 6.6, 7.3, 7.5, 7.2,
6.6, 5.7, 4.7, 3.7, 2.8, 2.1, 1.7, 1.8, 1.5, 1.6, 1.9, 2.2, 3.5,
2.8, 4.2, 4.2, 3.9, 4, 4, 4.1, 4, 4.1, 4.2, 4.2, 4.3, 4.7, 4.5,
4.3, 4.3, 4.6, 4.6, 4.7, 4.5, 4.5, 3, 2.8, 2.5, 2.8, 3.2, 3.1,
2.6, 3.2, 2.9, 2.6, 2.8, 2.6, 3.4, 2.8, 2.4, 3, 3.1, 3, 3.5,
2.9, 3.3, 3.3, 3.1, 3.4, 3.1, 3.2, 3.3, 3.6, 3.6, 3.5, 3.6, 3.9,
3.8, 3.9, 4.1, 4, 4.3, 4.5, 3.9, 4.5, 4.1, 4.1, 3.6, 3.7, 3.4,
3.6, 3.5, 3.9, 3.9, 3.6, 4, 4.5, 4.5, 4, 4.2, 4.3, 4.4, 4.3,
4.2, 4.4, 5, 4.6, 4.9, 5.1, 5.2, 5.1, 4.9, 4.8, 4.7, 4.6, 4.8,
5, 4.8, 4.6, 4.5, 4.6, 4.6, 4.8, 4.7, 4.7, 4.5, 4.8, 4.6, 5.2,
5.3, 5.1, 5, 5, 4.8, 4.7, 5.1, 5.6, 5.5, 5.1, 5, 5.3, 5.3, 4.9,
4.8, 4.8, 6.2, 6.3, 6.3, 6.2, 6.1, 6, 5.4, 5.6, 4.3, 5.2, 4.5,
4.7, 4.5, 4.4, 4.2, 4.2, 4.1, 4.2, 4.3, 4.5, 3.3, 3.8, 3.8, 3.8,
3.9, 3.5, 3.8, 3.9, 3.8, 3.9, 4.6, 5.3, 4.7, 4.4, 4.4, 5, 5.3,
4.9, 4.5, 4.5, 5.5, 5.5, 5.4, 5, 5, 5, 5, 4.8, 4.8, 4.8, 4.6,
4.8, 5.4, 5.3, 5.3, 4.9, 5, 5, 4.9, 5, 3.2, 3.2, 2.9, 3.3, 3.4,
3.2, 3.1, 3.1, 3.3, 3.4, 3.4, 3.5, 3.5, 3.8, 3.8, 3.1, 3.3, 3.8,
3.1, 3.5), Region = c("South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "South Asia", "South Asia", "South Asia",
"South Asia", "South Asia", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region",
"Region", "Region", "Region", "Region", "Region", "Region", "Region"
)), row.names = c(NA, -360L), class = "data.frame")
2 個解決方案
解決方案1
1 已采納 2020-09-26 12:08:31
問題是， geom_dl使用的值gedu在你的數據集，並通過計算不擬合值geom_smooth 。
我試過
將
stat="smooth"傳遞給geom_dl導致圖上沒有出現標簽使用帶有
geom="text"stat_smooth在端點手動添加標簽，但不起作用
因此，我能找到的唯一解決方案是手動計算擬合值，然后可以將其映射到geom_dl y上。 用於計算擬合值我
-
tidyr::nest按Country和Regiontidyr::nestdf - 使用
purrr::map和broom::augment進行估計並獲得擬合值 -
tidyr::unnest並只保留所需的列
library(ggplot2)
library(directlabels)
library(purrr)
library(broom)
library(tidyr)
library(dplyr)
gedu5 %>%
# Manually compute the fitted values
nest(data = -c(Region, Country)) %>%
mutate(mod = map(data, ~ lm(gedu ~ poly(Year, 3), data = .x)),
mod = map2(mod, data, augment)) %>%
unnest(mod) %>%
select(Country, Region, Year, gedu, .fitted) %>%
ggplot(aes(x = Year, y = gedu, colour = Country, group = Country)) +
geom_smooth(method = "lm", formula = y ~ poly(x, 3), se = FALSE) +
geom_dl(aes(y = .fitted, label = Country), method = list(dl.combine("first.points", "last.points"), cex = 1)) +
geom_point(stat = "identity") +
scale_colour_discrete(guide = "none") +
labs(title = "Government expenditure on education, total (% of GDP)", cex.main = 2.5) +
theme(axis.title = element_blank()) +
facet_wrap(.~Region, 2, scales="free")
解決方案2
1 2020-09-26 12:26:09
這是一種通過為directlabels創建自定義method來directlabels method 。
自定義方法是帶有參數d和...函數，它們返回一個數據框。 d是一個包含x 、 y 、 groups和一些其他列的數據框。
創建一個為每個組創建lm的自定義方法。 保留第一個和最后一個值並適當設置hjust 。
library(tidyverse)
library(directlabels)
first_last_poly3 <- function(d, ...) {
d %>%
group_by(groups) %>%
group_modify(function(g, ...) {
mutate(g, y = predict(lm(y ~ poly(x, 3), data = g)))
}) %>%
filter(row_number() %in% c(1, n())) %>%
mutate(hjust = ifelse(row_number() == 1, 1, 0))
}
創建繪圖並使用first_last_poly3作為geom_dl method 。
ggplot(gedu5, aes(x = Year, y = gedu, colour = Country, group = Country)) +
geom_smooth(method = "lm", formula = y ~ poly(x, 3), se = FALSE)+
geom_point(stat = "identity") +
scale_colour_discrete(guide = 'none') +
geom_dl(aes(label = Country), method = first_last_poly3) +
labs(title = "Government expenditure on education, total (% of GDP)", cex.main = 2.5) +
theme(axis.title = element_blank()) +
facet_wrap(.~Region, 2, scales="free")
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r ggplot2如何在geom_text中調整角度，將標簽放置在條形底部
[英]r ggplot2 How to make vjust in geom_text put label at bottom of bar
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r ggplot2如何在geom_text中調整角度，將標簽放置在條形底部
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