插入一个R visualization:编辑器
必定要确保图形出现这个model的小图标,表明这个R visualization的模型数据成功绑定以后才能进行下一步操做:ide
模型绑定成功后,在R script编辑器Environment标签页的Data下拉菜单里能看到模型数据。ui
使用这个SAP Analytics Cloud官方教程里提供的excel文件做为数据源:url
https://www.sapanalytics.clou...spa
该excel内容以下:excel
excel系统导入SAP Analytics Cloud后,须要使用simple transformation,将;分号分隔的值拆分红三列:code
逐一拆分:orm
拆分完毕以后,生成Model. 将这个url里包含的R脚本复制粘贴到R编辑器里:
https://www.sapanalytics.clou...blog
# Discription: # Creating a histogram of the log returns, adding the kernel density of the log returns # and the normal density as reference distribution # # Requirements: # ggplot requires a data frame # # Output: # Histogram Plot # library(ggplot2) Simulated_data <- data.frame(Simulated_data) histgg <- ggplot(data = Simulated_data, aes(logreturns)) histgg + geom_histogram(aes(y = ..density..),fill = "lightblue",color = "black", alpha = 0.8, position = "identity") + geom_density(aes(color = "Kernel Density"), size = 1) + stat_function(aes(color = "Normal Distribution"), fun = dnorm, args = list(mean = mean(Simulated_data$logreturns), sd = sd(Simulated_data$logreturns)), size = 1) + ggtitle("Histogram") + theme(panel.grid = element_line(linetype = "dashed", color = "lightgrey"), panel.background = element_rect(fill = "white"), panel.border = element_rect(colour = "black", fill=NA), plot.title = element_text(hjust = 0.5)) + scale_colour_manual("Density", values = c("red", "darkgreen")) + xlab(" ")+ ylab("Frequency")
点击Execute按钮,就能够看到R脚本绘制出来的图形了:教程
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