绘图技巧 | 议会(项目)图还不会做？快上车~~
好奇心Log 今天
以下文章来源于DataCharm ，作者宁海涛
DataCharm定期更新 数据分析、数据可视化(商业、学术图表)教程，同时也会涉及机器学习、深度学习模型的构建及应用。所用工具主要包括Python、R、Processing等。
今天这篇推文小编给大家介绍一个一直想绘制的图表-议会图(parliament diagrams),当然这也是柱形图系列变形的一种。绘制这种图表也是超级简单的，只需使用R-ggpol包进行绘制即可，当然，改包还提供其他优秀的绘图函数，下面就一起来看下吧。
R-ggpol包简介 R-ggpol包实例介绍(议会图为主)
R-ggpol包简介
官网：
https://github.com/erocoar/ggpol
绘图函数
作为ggplot2绘图系统中的一员，其安装方便(RStudio直接搜索安装即可)而且还可以通过ggplot2强大的绘图函数设计出自己的可视化作品。其提供的主要绘图函数如下：
geom_arcbar(): 绘制跨越180度的弧形条形图。 geom_parliament(): 绘制议会图(parliament diagrams)，即圆弧上的圆圈，其中每个圆圈代表一个议会议员。指定了fill或color即可进行填充和颜色的映射。 geom_circle(): 绘制具有指定半径的圆多边形,注意和ggplot2的geom_point()区分开。 geom_tshighlight(): 可对绘制时间序列的图表进行突出作用，也是比较常用的绘图技巧。 geom_boxjitter(): 绘制了一个混合箱形图-半箱形图且带有误差线的图。
R-ggpol包实例介绍
「geom_boxjitter」:
(绘制了一个混合箱形图-半箱形图且带有误差线的图)
library(ggpol)library(tidyverse)library(ggtext)library(hrbrthemes)library(LaCroixColoR)
library(ggsci) # 使用科学系配色df <- data.frame(score = rgamma(150, 4, 1), gender = sample(c("M", "F"), 150, replace = TRUE), genotype = factor(sample(1:3, 150, replace = TRUE)))
boxjitter <- ggplot(df) + geom_boxjitter(aes(x = genotype, y = score, fill = gender), jitter.shape = 21, jitter.color = NA, jitter.height = 0, jitter.width = 0.04, outlier.color = NA, errorbar.draw = TRUE) + ggsci::scale_fill_jco() + labs( title = "Example of <span style='color:#D20F26'>ggpol::geom_boxjitter function</span>", subtitle = "processed charts with <span style='color:#1A73E8'>geom_boxjitter()</span>", caption = "Visualization by <span style='color:#DD6449'>DataCharm</span>") + hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") + theme( plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black", size = 20, margin = margin(t = 1, b = 12)), plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15), plot.caption = element_markdown(face = 'bold',size = 12) )顺便提一下，很喜欢sci包的这个配色，特适合绘制科研图表哦~~
「geom_tshighlight」
(可对绘制时间序列的图表进行突出作用，也是比较常用的绘图技巧.)
time_hlight <- ggplot(economics, aes(x = date, y = unemploy)) + geom_line() + geom_tshighlight(aes(xmin = as.Date("01/01/1990", format = "%d/%m/%Y"), xmax = as.Date("01/01/2000", format = "%d/%m/%Y")), alpha = 0.01) + labs( title = "Example of <span style='color:#D20F26'>ggpol::geom_tshighlight function</span>", subtitle = "processed charts with <span style='color:#1A73E8'>geom_tshighlight()</span>", caption = "Visualization by <span style='color:#DD6449'>DataCharm</span>") + hrbrthemes::theme_ft_rc(base_family = "Roboto Condensed") + theme( plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black", size = 20, margin = margin(t = 1, b = 12)), plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15), plot.caption = element_markdown(face = 'bold',size = 12) )这里使用了hrbrthemes::theme_ft_rc()主题风格(暗黑系列)，也是小编较常用的主题哦~~
「geom_arcbar」
绘制跨越180度的弧形条形图。
#构建数据test_data_bt <- data.frame( parties = factor(c("CDU", "CSU", "AfD", "FDP", "SPD", "Linke", "Gruene", "Fraktionslos"), levels = c("CDU", "CSU", "AfD", "FDP", "SPD", "Linke", "Gruene", "Fraktionslos")), seats = c(200, 46, 92, 80, 153, 69, 67, 2), # colors = c("black", "blue", "lightblue", "yellow", "red", # "purple", "green", "grey"), stringsAsFactors = FALSE)
arcbar <- ggplot(test_data_bt) + geom_arcbar(aes(shares = seats, r0 = 5, r1 = 10, fill = parties), color="gray50" ,sep = 0.1) + #scale_fill_manual(values = bt$colors) + scale_fill_manual(values = lacroix_palette(type = "paired"))+ coord_fixed() + # 修改图例 guides(fill=guide_legend(nrow=2,byrow=TRUE,reverse = TRUE,title=NULL))+ # theme_void(base_family = "Roboto Condensed") + labs( title = "Example of <span style='color:#D20F26'>ggpol::geom_arcbar function</span>", subtitle = "processed charts with <span style='color:#1A73E8'>geom_arcbar()</span>", caption = "Visualization by <span style='color:#DD6449'>DataCharm</span>") + hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") + theme( plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black", size = 20, margin = margin(t = 1, b = 12)), plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15), plot.caption = element_markdown(face = 'bold',size = 12), # 去除刻度线和网格线 axis.text.x = element_blank(), axis.text.y = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_rect(fill="#FEFBCD"), panel.border = element_rect(fill = NA,colour = "#FEFBCD"), plot.background = element_rect(fill="#FEFBCD",colour = "#FEFBCD"), # 修改图例参数 legend.position = 'bottom', legend.direction = "horizontal", legend.spacing.y = unit(0.1,"cm"), legend.spacing.x = unit(0.1,"cm"), legend.key.size = unit(0.8, 'lines'), legend.text = element_text(margin = margin(r = .5, unit = 'cm')) )这里我们在hrbrthemes::theme_ipsum() 主题基础上进行了一些修改，具体代码中均有解释。
「geom_parliament」
议会(项目)图(parliament diagrams)
library(readxl)
df<-read_excel("test.xlsx")#head(df)df1<-df%>%group_by(Party)%>%summarise(Seats=sum(Seats))%>%arrange(Seats) # 简单的数据处理df1$legend <- paste0(df1$Party,"(", df1$Seats,")") # 拼接字符串
parliament <- ggplot(data = df1) + geom_parliament(aes(seats = Seats,fill = Party),color="black") + scale_fill_manual(values = lacroix_palette(type = "paired"),labels=df1$legend) + # 修改图例 guides(fill=guide_legend(nrow=3,byrow=TRUE,reverse = TRUE,title=NULL))+ # 添加描述性文字 annotate("text", x = 0, y = 0.4, label = "Seats in the Parliament :\n 423 occupied \n 27 vacant", colour = "gray20",size=5) + labs( title = "Example of <span style='color:#D20F26'>ggpol::geom_parliament function</span>", subtitle = "processed charts with <span style='color:#1A73E8'>geom_parliament()</span>", caption = "Visualization by <span style='color:#DD6449'>DataCharm</span>") + hrbrthemes::theme_ipsum(base_family = "Roboto Condensed") + # 定制化主题 theme( plot.title = element_markdown(hjust = 0.5,vjust = .5,color = "black", size = 20, margin = margin(t = 1, b = 12)), plot.subtitle = element_markdown(hjust = 0,vjust = .5,size=15), plot.caption = element_markdown(face = 'bold',size = 12), # 去除刻度线和网格线 axis.text.x = element_blank(), axis.text.y = element_blank(), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_rect(fill="#FEFBCD"), panel.border = element_rect(fill = NA,colour = "#FEFBCD"), plot.background = element_rect(fill="#FEFBCD",colour = "#FEFBCD"), # 修改图例参数 legend.position = 'bottom', legend.direction = "horizontal", legend.spacing.y = unit(0.1,"cm"), legend.spacing.x = unit(0.1,"cm"), legend.key.size = unit(0.8, 'lines'), legend.text = element_text(margin = margin(r = .5, unit = 'cm')) )到这里呢，议会(项目)图(parliament diagrams)也就绘制完成了，虽然一些交互式工具(如Highcharts)也可快速绘制，而我们的目的还是进行细节、配色的练习哦~~
总结
本期推文终于介绍了小编一直心心念念的可视化图了，同时，小伙伴们也应知道的是，善用一些优秀的主题包和颜色包，可以使你的可视化作品颜值提升的不止一个档次哦~，好了，感兴趣的小伙伴赶快去练习下吧~~
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