插入一个R visualization：
一定要确保图形出现这个model的小图标，代表这个R visualization的模型数据成功绑定之后才能进行下一步操作：
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。
使用这个SAP Analytics Cloud官方教程里提供的excel文件作为数据源：
https://www.sapanalytics.cloud/tutorial-r-visualization/
该excel内容如下：
excel系统导入SAP Analytics Cloud后，需要使用simple transformation，将；分号分隔的值拆分成三列：
逐一拆分：
拆分完毕之后，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.cloud/wp-content/uploads/2019/09/R-Script-Plot.txt
# 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，就可以看到R脚本绘制出来的图形了：
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