ECharts,一個使用 JavaScript 實現的開源可視化庫,可以流暢的運行在 PC 和移動設備上,兼容當前絕大部分瀏覽器(IE8/9/10/11,Chrome,Firefox,Safari等),底層依賴矢量圖形庫 ZRender,提供直觀,交互豐富,可高度個性化定制的數據可視化圖表。
echarts4r 包是 ECharts 的 R 語言接口,目前可以從 CRAN 是直接安裝。echarts4r 語法結構簡單,易用,可讀性很好,是很好的交互式繪圖包。
安裝echarts4r包,具體操作見上篇
R包 安裝教程
教程下載:https://cran.r-project.org/web/packages/echarts4r/index.html
install.packages("echarts4r")
散點圖
echarts4r 作圖第一步用e_charts函數創建一個 echarts4r 對象,函數第一個參數為數據,第二個參數為 x 軸數據,第二步以及后續都是用%>%管道操作符來進一步作圖。
繪制散點圖,用iris數據,x 軸為 Sepal.Length。y 軸為 Petal.Length,在e_scatter中定義為serie。通過group_by根據 Sepal.Length 進行分組,在圖中表現為不同顏色。散點大小通過size參數設置。
library(echarts4r) iris %>% group_by(Species) %>% e_charts(x = Sepal.Length) %>% e_scatter(serie = Petal.Length, size = Sepal.Width)
對比一下 ggplot2 的散點圖語法及效果
library(ggplot2) iris %>% ggplot(aes(x=Sepal.Length,y=Petal.Length,size=Sepal.Width,col=Species))+ geom_point()
柱狀圖
library(echarts4r) df <- data.frame( x = seq(50), y = rnorm(50, 10, 3), z = rnorm(50, 11, 2), w = rnorm(50, 9, 2) ) df %>% e_charts(x) %>% e_bar(y, name = "bar") %>% e_title("Bar and step charts")
熱力圖
library(echarts4r) v <- LETTERS[1:10] matrix <- data.frame( x = sample(v, 300, replace = TRUE), y = sample(v, 300, replace = TRUE), z = rnorm(300, 10, 1), stringsAsFactors = FALSE ) %>% dplyr::group_by(x, y) %>% dplyr::summarise(z = sum(z)) %>% dplyr::ungroup() matrix %>% e_charts(x) %>% e_heatmap(y, z) %>% e_visual_map(z) %>% e_title("Heatmap")
儀表盤
library(echarts4r) e_charts() %>% e_gauge(41, "PERCENT") %>% e_title("Gauge")
詞雲
library(echarts4r) words <- function(n = 5000) { a <- do.call(paste0, replicate(5, sample(LETTERS, n, TRUE), FALSE)) paste0(a, sprintf("%04d", sample(9999, n, TRUE)), sample(LETTERS, n, TRUE)) } tf <- data.frame(terms = words(100), freq = rnorm(100, 55, 10)) %>% dplyr::arrange(-freq) tf %>% e_color_range(freq, color) %>% e_charts() %>% e_cloud(terms, freq, color, shape = "circle", sizeRange = c(3, 15)) %>% e_title("Wordcloud", "Random strings")
echarts4r 教程下載:https://cran.r-project.org/web/packages/echarts4r/index.html