r 聚合多因子变量

Question

我有一个这样的数据框：

    data.frame(home=c("A","B","C","A","C"),weight=c(0.1,0.25,0.36,0.14,0.2),region=c("north","south","east","North","south"))

Home Weigth  region  
A     0.1     North      
B     0.25    South    
C     0.36    East   
A     0.14    North
C     0.2     South

我想按照两个因素变量汇总我的 data.frame 并对第三个变量求和。结果将给出：

    data.frame(home=c("A","B","C"),north=c(0.24,0,0),south=c(0,0.25,0.2),east=c(0.36,0,0))

Home North  South  East
A     0.24   0      0
B     0      0.25    0
C     0      0.2    0.36

我正在尝试使用聚合等快速简便的功能，但也许唯一的解决方案是使用我想要的手动制作 data.frame

Answer 1

基本上有两个步骤，（1）汇总和； (2) 将结果转换为双向表

library(dplyr)
df <-  data.frame(home=c("A","B","C","A","C"),weight=c(0.1,0.25,0.36,0.14,0.2),region=c("north","south","east","North","south"))
df$region <- Hmisc::capitalize(as.character(df$region))

df_sum <- df %>% group_by(home, region) %>% summarize(weight_sum = sum(weight, na.rm=TRUE))

reshape2::dcast(df_sum, home ~ region, function(V) sum(V, na.rm=TRUE))

第二个和是无关的，也不是很必要，我放在这里只是为了避免将NA转换为0的额外步骤。

Answer 2

我想这样就可以了，h01 是你想要的结果

x00<-data.frame(home=c("A","B","C","A","C"),weight=c(0.1,0.25,0.36,0.14,0.2),
                region=c("north","South","East","North","South"),stringsAsFactors = F)
x00$region<-tolower(x00$region)
x01<-ddply(x00,.(region,home),summarize,result=sum(weight))
h01<-data.frame(north=c(0,0,0),south=c(0,0,0),east=c(0,0,0),row.names = c("A","B","C"))
for (x in 1:nrow(x01)){
  h01[x01$home[x],x01$region[x]]=x01$result[x]
}

h01$Home=row.names(h01)
row.names(h01)<-c()

Answer 3

数据

df <-  data.frame(
    home = c("A", "B", "C", "A", "C"),
    weight = c(0.1, 0.25, 0.36, 0.14, 0.2),
    region = c("north", "south", "east", "North", "south")
  )

整理

library(tidyr)
spread(df, region, weight, fill = 0)

重塑2

library(reshape2)
dcast(df, home ~ region, value.var = "weight", fill = 0)

基础

# xtabs
xtabs(weight ~ home + region, data = df) 

# reshape
df_wide <-reshape(df, idvar ='home', timevar ='region', direction ='wide')
df_wide[is.na(df_wide)] <- 0

输出

  home east north North south
1    A 0.00   0.1  0.14  0.00
2    B 0.00   0.0  0.00  0.25
3    C 0.36   0.0  0.00  0.20