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R语言 交互式绘图echarts4r包初探

 echarts4r 包是R 语言访问/调用百度ECharts的接口,语法结构简单,可读性强,是很好的交互式绘图包。”


01

打样


上图1


# install.packages("echarts4r")library(echarts4r)
df <- data.frame( x = seq(50), y = rnorm(50, 10, 3), z = rnorm(50, 11, 2), w = rnorm(50, 9, 2))
# > head(df)# x y z w# 1 1 14.681910 8.655808 8.986928# 2 2 8.738652 10.663773 13.174984# 3 3 6.350329 12.576939 8.227128# 4 4 10.699079 10.900659 10.503904# 5 5 12.909827 10.253127 12.261691# 6 6 7.376608 15.973790 8.305172
#图1df %>% e_charts(x) %>% e_line(z) %>% e_area(w) %>% e_title("Line and area charts")




02


散点图/Scatter

R语言 交互式绘图echarts4r包初探

上图2

R语言 交互式绘图echarts4r包初探

上图3


# df <- data.frame(# x = seq(50),# y = rnorm(50, 10, 3),# z = rnorm(50, 11, 2),# w = rnorm(50, 9, 2)# )
# 图2df %>% e_charts(x) %>% #初始化并设置x e_scatter(y) #设置scatter类型和y
# 图3df %>% e_charts(x) %>% #初始化并设置x轴变量  e_scatter(y, z) ##设置scatter类型、y变量和点大小z





03


桑基图/Sankey


R语言 交互式绘图echarts4r包初探

上图4


sankey <- data.frame( source = c("a", "b", "c", "d", "c"), target = c("b", "c", "d", "e", "e"), value = ceiling(rnorm(5, 10, 1)), stringsAsFactors = FALSE)
sankey %>% e_charts() %>% e_sankey(source, target, value) %>% e_title("Sankey chart")



04


三维/3D

上图5

#图5v <- LETTERS[1:10]matrix <- data.frame( x = sample(v, 300, replace = TRUE),  y = sample(v, 300, replace = TRUE),  z = rnorm(300, 10, 1), color = rnorm(300, 10, 1), size = rnorm(300, 10, 1), stringsAsFactors = FALSE) %>%  dplyr::group_by(x, y) %>%  dplyr::summarise( z = sum(z), color = sum(color), size = sum(size) ) %>%  dplyr::ungroup()
matrix %>% e_charts(x) %>% e_scatter_3d(y, z, size, color) %>% e_visual_map( size, inRange = list(symbolSize = c(1, 30)), # scale size dimension = 3 # third dimension 0 = x, y = 1, z = 2, size = 3 ) %>% e_visual_map( color, inRange = list(color = c('#bf444c', '#d88273', '#f6efa6')), # scale colors dimension = 4, # third dimension 0 = x, y = 1, z = 2, size = 3, color = 4 bottom = 300 # padding to avoid visual maps overlap )



参考:echarts4r说明书

https://echarts4r.john-coene.com/articles/chart_types.html





【往期回顾推荐】







《R数据科学》是一本专门讲解tidyverse相关包的书籍,主要涉及dplyr、tidyr、ggplot2、purrr等,非常值得学习,基本上此一本书可以解答数据处理的大部分问题