使用 ggplot2 Rstudio 进行时间序列可视化(国家级)
Time series visualization with ggplot2 Rstudio (country-level)
我刚刚在学习 R 基础知识,我想请您帮忙处理数据可视化,尤其是时间序列。我正在研究从 2009 年到 2019 年每个国家/地区特定类别政党(右翼民粹主义者)的投票份额如何随着时间的推移而变化。
这是我的数据集:
dput(votesharespop)
structure(list(country = c("Austria", "Belgium", "Bulgaria",
"Czech Republic", "Denmark", "Estonia", "Finland", "France",
"Germany", "Great Britain", "Greece", "Hungary", "Italy", "Lithuania",
"Luxembourg", "Netherlands", "Poland", "Romania", "Portugal",
"Slovakia", "Slovenia", "Spain", "Sweden", "Austria", "Belgium",
"Bulgaria", "Czech Republic", "Denmark", "Estonia", "Finland",
"France", "Germany", "Great Britain", "Greece", "Hungary", "Italy",
"Lithuania", "Luxembourg", "Netherlands", "Poland", "Romania",
"Portugal", "Slovakia", "Slovenia", "Spain", "Sweden", "Austria",
"Belgium", "Bulgaria", "Czech Republic", "Denmark", "Estonia",
"Finland", "France", "Germany", "Great Britain", "Greece", "Hungary",
"Italy", "Lithuania", "Luxembourg", "Netherlands", "Poland",
"Romania", "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden"
), year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019), vote_share = c(17.3, 15.7, 16.7,
4.3, 15.3, 0, 9.8, 8.1, 1.7, 22.7, 7.2, 71.2, 45.5, 12.2, 7.4,
17, 27.4, 8.7, 0, 5.6, 35.2, 0, 3.3, 20.2, 7.6, 16.8, 4.8, 26.6,
5.3, 12.9, 28.7, 0.4, 28.6, 6.2, 66.2, 26.7, 14.3, 7.5, 13.3,
31.8, 2.7, 0, 3.6, 28.8, 1.6, 9.7, 17.2, 13.8, 14.6, 10, 10.8,
12.7, 13.8, 26.8, 11, 34.9, 6.2, 62.2, 49.5, 2.7, 10, 14.5, 49.1,
0, 1.5, 7.3, 30.3, 6.2, 15.3), continent = c("Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -69L))
我的目标是得到这样的东西(没有互动):
或类似方面的内容,但适用于每个国家/地区。
非常感谢您的关注。
数据
votesharespop <- structure(list(country = c("Austria", "Belgium", "Bulgaria",
"Czech Republic", "Denmark", "Estonia", "Finland", "France",
"Germany", "Great Britain", "Greece", "Hungary", "Italy", "Lithuania",
"Luxembourg", "Netherlands", "Poland", "Romania", "Portugal",
"Slovakia", "Slovenia", "Spain", "Sweden", "Austria", "Belgium",
"Bulgaria", "Czech Republic", "Denmark", "Estonia", "Finland",
"France", "Germany", "Great Britain", "Greece", "Hungary", "Italy",
"Lithuania", "Luxembourg", "Netherlands", "Poland", "Romania",
"Portugal", "Slovakia", "Slovenia", "Spain", "Sweden", "Austria",
"Belgium", "Bulgaria", "Czech Republic", "Denmark", "Estonia",
"Finland", "France", "Germany", "Great Britain", "Greece", "Hungary",
"Italy", "Lithuania", "Luxembourg", "Netherlands", "Poland",
"Romania", "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden"
), year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019), vote_share = c(17.3, 15.7, 16.7,
4.3, 15.3, 0, 9.8, 8.1, 1.7, 22.7, 7.2, 71.2, 45.5, 12.2, 7.4,
17, 27.4, 8.7, 0, 5.6, 35.2, 0, 3.3, 20.2, 7.6, 16.8, 4.8, 26.6,
5.3, 12.9, 28.7, 0.4, 28.6, 6.2, 66.2, 26.7, 14.3, 7.5, 13.3,
31.8, 2.7, 0, 3.6, 28.8, 1.6, 9.7, 17.2, 13.8, 14.6, 10, 10.8,
12.7, 13.8, 26.8, 11, 34.9, 6.2, 62.2, 49.5, 2.7, 10, 14.5, 49.1,
0, 1.5, 7.3, 30.3, 6.2, 15.3), continent = c("Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -69L))
代码
library(ggplot2)
library(ggthemes) # to access theme_hc()
ggplot(data = votesharespop, mapping = aes(x = year, y = vote_share, color = country)) + # specify data, x-axis, y-axis and grouping variable
geom_line() + # a line per group
geom_point() + # points per group
theme_hc() + # a ggtheme, similar to your example
labs(title = "Variation of vote shares of right wing populists, 2009 to 2019", # plot title
subtitle = "Add a subtitle of your choice", # plot subtitle
caption = "Add a caption of your choice") + # plot caption
theme(legend.position = "right", # move legend to the right hand side of the plot
axis.title.x = element_blank(), # remove x axis title
axis.title.y = element_blank(), # remove y axis title
legend.title = element_blank(), # remove legend title
plot.title = element_text(size = 20, color = "gray40"), # change size and color of plot title
plot.subtitle = element_text(color = "gray40"), # change color of subtitle
plot.caption = element_text(color = "gray40", hjust = 0)) + # change color of caption and left-align
scale_y_continuous(breaks = seq(0, 80, by = 20)) + # specify min, max and break distance for y axis
scale_x_continuous(breaks = seq(2009, 2019, by = 5)) + # specify min, max and break distance for x axis
expand_limits(y = c(0, 80))
输出
但是请注意,对于多个组,颜色可能很难区分。最好使用 facet_wrap
代码
ggplot(data = votesharespop, mapping = aes(x = year, y = vote_share, color = country)) + # specify data, x-axis, y-axis and grouping variable
geom_line() + # a line per group
geom_point() + # points per group
theme_hc() + # a ggtheme, similar to your example
labs(title = "Variation of vote shares of right wing populists, 2009 to 2019", # plot title
subtitle = "Add a subtitle of your choice", # plot subtitle
caption = "Add a caption of your choice") + # plot caption
theme(legend.position = "right", # move legend to the right hand side of the plot
axis.title.x = element_blank(), # remove x axis title
axis.title.y = element_blank(), # remove y axis title
legend.title = element_blank(), # remove legend title
plot.title = element_text(size = 20, color = "gray40"), # change size and color of plot title
plot.subtitle = element_text(color = "gray40"), # change color of subtitle
plot.caption = element_text(color = "gray40", hjust = 0)) + # change color of caption and left-align
scale_y_continuous(breaks = seq(0, 75, by = 25)) + # specify min, max and break distance for y axis
scale_x_continuous(breaks = seq(2009, 2019, by = 5)) + # specify min, max and break distance for x axis
expand_limits(y = c(0, 75)) + # adjust y axis limits
facet_wrap(~ country) + # facet wrap
theme(legend.position = "none") + # remove legend, since not needed anymore in facet_wrap
theme(panel.spacing.x = unit(4, "mm")) # avoid overlapping of x axis text
输出
我刚刚在学习 R 基础知识,我想请您帮忙处理数据可视化,尤其是时间序列。我正在研究从 2009 年到 2019 年每个国家/地区特定类别政党(右翼民粹主义者)的投票份额如何随着时间的推移而变化。 这是我的数据集:
dput(votesharespop)
structure(list(country = c("Austria", "Belgium", "Bulgaria",
"Czech Republic", "Denmark", "Estonia", "Finland", "France",
"Germany", "Great Britain", "Greece", "Hungary", "Italy", "Lithuania",
"Luxembourg", "Netherlands", "Poland", "Romania", "Portugal",
"Slovakia", "Slovenia", "Spain", "Sweden", "Austria", "Belgium",
"Bulgaria", "Czech Republic", "Denmark", "Estonia", "Finland",
"France", "Germany", "Great Britain", "Greece", "Hungary", "Italy",
"Lithuania", "Luxembourg", "Netherlands", "Poland", "Romania",
"Portugal", "Slovakia", "Slovenia", "Spain", "Sweden", "Austria",
"Belgium", "Bulgaria", "Czech Republic", "Denmark", "Estonia",
"Finland", "France", "Germany", "Great Britain", "Greece", "Hungary",
"Italy", "Lithuania", "Luxembourg", "Netherlands", "Poland",
"Romania", "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden"
), year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019), vote_share = c(17.3, 15.7, 16.7,
4.3, 15.3, 0, 9.8, 8.1, 1.7, 22.7, 7.2, 71.2, 45.5, 12.2, 7.4,
17, 27.4, 8.7, 0, 5.6, 35.2, 0, 3.3, 20.2, 7.6, 16.8, 4.8, 26.6,
5.3, 12.9, 28.7, 0.4, 28.6, 6.2, 66.2, 26.7, 14.3, 7.5, 13.3,
31.8, 2.7, 0, 3.6, 28.8, 1.6, 9.7, 17.2, 13.8, 14.6, 10, 10.8,
12.7, 13.8, 26.8, 11, 34.9, 6.2, 62.2, 49.5, 2.7, 10, 14.5, 49.1,
0, 1.5, 7.3, 30.3, 6.2, 15.3), continent = c("Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -69L))
我的目标是得到这样的东西(没有互动):
或类似方面的内容,但适用于每个国家/地区。
非常感谢您的关注。
数据
votesharespop <- structure(list(country = c("Austria", "Belgium", "Bulgaria",
"Czech Republic", "Denmark", "Estonia", "Finland", "France",
"Germany", "Great Britain", "Greece", "Hungary", "Italy", "Lithuania",
"Luxembourg", "Netherlands", "Poland", "Romania", "Portugal",
"Slovakia", "Slovenia", "Spain", "Sweden", "Austria", "Belgium",
"Bulgaria", "Czech Republic", "Denmark", "Estonia", "Finland",
"France", "Germany", "Great Britain", "Greece", "Hungary", "Italy",
"Lithuania", "Luxembourg", "Netherlands", "Poland", "Romania",
"Portugal", "Slovakia", "Slovenia", "Spain", "Sweden", "Austria",
"Belgium", "Bulgaria", "Czech Republic", "Denmark", "Estonia",
"Finland", "France", "Germany", "Great Britain", "Greece", "Hungary",
"Italy", "Lithuania", "Luxembourg", "Netherlands", "Poland",
"Romania", "Portugal", "Slovakia", "Slovenia", "Spain", "Sweden"
), year = c(2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009, 2009,
2009, 2009, 2009, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014, 2014,
2014, 2014, 2014, 2014, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019, 2019,
2019, 2019, 2019, 2019, 2019), vote_share = c(17.3, 15.7, 16.7,
4.3, 15.3, 0, 9.8, 8.1, 1.7, 22.7, 7.2, 71.2, 45.5, 12.2, 7.4,
17, 27.4, 8.7, 0, 5.6, 35.2, 0, 3.3, 20.2, 7.6, 16.8, 4.8, 26.6,
5.3, 12.9, 28.7, 0.4, 28.6, 6.2, 66.2, 26.7, 14.3, 7.5, 13.3,
31.8, 2.7, 0, 3.6, 28.8, 1.6, 9.7, 17.2, 13.8, 14.6, 10, 10.8,
12.7, 13.8, 26.8, 11, 34.9, 6.2, 62.2, 49.5, 2.7, 10, 14.5, 49.1,
0, 1.5, 7.3, 30.3, 6.2, 15.3), continent = c("Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe", "Europe", "Europe", "Europe",
"Europe", "Europe", "Europe", "Europe")), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -69L))
代码
library(ggplot2)
library(ggthemes) # to access theme_hc()
ggplot(data = votesharespop, mapping = aes(x = year, y = vote_share, color = country)) + # specify data, x-axis, y-axis and grouping variable
geom_line() + # a line per group
geom_point() + # points per group
theme_hc() + # a ggtheme, similar to your example
labs(title = "Variation of vote shares of right wing populists, 2009 to 2019", # plot title
subtitle = "Add a subtitle of your choice", # plot subtitle
caption = "Add a caption of your choice") + # plot caption
theme(legend.position = "right", # move legend to the right hand side of the plot
axis.title.x = element_blank(), # remove x axis title
axis.title.y = element_blank(), # remove y axis title
legend.title = element_blank(), # remove legend title
plot.title = element_text(size = 20, color = "gray40"), # change size and color of plot title
plot.subtitle = element_text(color = "gray40"), # change color of subtitle
plot.caption = element_text(color = "gray40", hjust = 0)) + # change color of caption and left-align
scale_y_continuous(breaks = seq(0, 80, by = 20)) + # specify min, max and break distance for y axis
scale_x_continuous(breaks = seq(2009, 2019, by = 5)) + # specify min, max and break distance for x axis
expand_limits(y = c(0, 80))
输出
但是请注意,对于多个组,颜色可能很难区分。最好使用 facet_wrap
代码
ggplot(data = votesharespop, mapping = aes(x = year, y = vote_share, color = country)) + # specify data, x-axis, y-axis and grouping variable
geom_line() + # a line per group
geom_point() + # points per group
theme_hc() + # a ggtheme, similar to your example
labs(title = "Variation of vote shares of right wing populists, 2009 to 2019", # plot title
subtitle = "Add a subtitle of your choice", # plot subtitle
caption = "Add a caption of your choice") + # plot caption
theme(legend.position = "right", # move legend to the right hand side of the plot
axis.title.x = element_blank(), # remove x axis title
axis.title.y = element_blank(), # remove y axis title
legend.title = element_blank(), # remove legend title
plot.title = element_text(size = 20, color = "gray40"), # change size and color of plot title
plot.subtitle = element_text(color = "gray40"), # change color of subtitle
plot.caption = element_text(color = "gray40", hjust = 0)) + # change color of caption and left-align
scale_y_continuous(breaks = seq(0, 75, by = 25)) + # specify min, max and break distance for y axis
scale_x_continuous(breaks = seq(2009, 2019, by = 5)) + # specify min, max and break distance for x axis
expand_limits(y = c(0, 75)) + # adjust y axis limits
facet_wrap(~ country) + # facet wrap
theme(legend.position = "none") + # remove legend, since not needed anymore in facet_wrap
theme(panel.spacing.x = unit(4, "mm")) # avoid overlapping of x axis text
输出