我的目标是使用googleVis
包在R中制作多个Sankey。输出应该类似于:
我在R:
中创建了一些虚拟数据set.seed(1)
source <- sample(c("North","South","East","West"),100,replace=T)
mid <- sample(c("North ","South ","East ","West "),100,replace=T)
destination <- sample(c("North","South","East","West"),100,replace=T) # N.B. It is important to have a space after the second set of destinations to avoid a cycle
dummy <- rep(1,100) # For aggregation
dat <- data.frame(source,mid,destination,dummy)
aggdat <- aggregate(dummy~source+mid+destination,dat,sum)
如果我只有一个源和目的地,我可以建立一个有2个变量的Sankey,但不是中间点:
aggdat <- aggregate(dummy~source+destination,dat,sum)
library(googleVis)
p <- gvisSankey(aggdat,from="source",to="destination",weight="dummy")
plot(p)
代码产生了这个:
如何修改
p <- gvisSankey(aggdat,from="source",to="destination",weight="dummy")
也接受mid
变量?
答案 0 :(得分:8)
函数gvisSankey
确实直接接受中级。这些级别必须在底层数据中编码。
source <- sample(c("NorthSrc", "SouthSrc", "EastSrc", "WestSrc"), 100, replace=T)
mid <- sample(c("NorthMid", "SouthMid", "EastMid", "WestMid"), 100, replace=T)
destination <- sample(c("NorthDes", "SouthDes", "EastDes", "WestDes"), 100, replace=T)
dummy <- rep(1,100) # For aggregation
现在,我们将重塑原始数据:
library(dplyr)
datSM <- dat %>%
group_by(source, mid) %>%
summarise(toMid = sum(dummy) ) %>%
ungroup()
数据框datSM
总结了从Source到Mid的单位数。
datMD <- dat %>%
group_by(mid, destination) %>%
summarise(toDes = sum(dummy) ) %>%
ungroup()
数据框datMD
汇总了从中间到目的地的单位数。该数据帧将被添加到最终数据帧中。数据框必须为ungroup
并且具有相同的colnames
。
colnames(datSM) <- colnames(datMD) <- c("From", "To", "Dummy")
由于datMD
被追加为最后一个,gvisSankey
会自动识别中间步骤。
datVis <- rbind(datSM, datMD)
p <- gvisSankey(datVis, from="From", to="To", weight="dummy")
plot(p)