[英]Formatting data in R categorical
Let 让
reason <- c("v","v","v","v","v","s","s","s","v","v","v","s","s")
location <- c("c","c","c","c","c","c","c","c","h","h","h","h","h")
zero_one <- c(1,1,0,1,1,1,1,0,1,0,0,1,0)
df <- data.frame(reason, location, zero_one)
Is there an easy way to convert "df" to "DF", where "DF" has the following shape: 有没有一种简单的方法可以将“ df”转换为“ DF”,其中“ DF”具有以下形状:
reason location #zeros #ones
v c 1 4
s c 1 2
v h 2 1
s h 1 1
You could do this using dcast
您可以使用dcast
进行此操作
library(reshape2)
dcast(transform(df, zero_one= factor(zero_one, levels=0:1,
labels=c('zeros', 'ones'))), ...~zero_one, value.var='zero_one', length)
# reason location zeros ones
#1 s c 1 2
#2 s h 1 1
#3 v c 1 4
#4 v h 2 1
Or using data.table
(similar approach as @jalapic's) 或使用data.table
(与data.table
相似的方法)
setDT(df)[,list(zeros=sum(!zero_one), ones=sum(!!zero_one)),
.(reason, location)][]
# reason location zeros ones
#1: v c 1 4
#2: s c 1 2
#3: v h 2 1
#4: s h 1 1
Or in base R
或以base R
为base R
aggregate(cbind(zeros=!zero_one, ones=!!zero_one)~., df, FUN= sum)
# reason location zeros ones
#1 s c 1 2
#2 v c 1 4
#3 s h 1 1
#4 v h 2 1
You can do it with dplyr
very simply: 您可以使用dplyr
:
library(dplyr)
df %>%
group_by(reason,location) %>%
summarize(zeros = sum(zero_ones==0), ones = sum(zero_ones==1))
# reason location zeros ones
#1 s c 1 2
#2 s h 1 1
#3 v c 1 4
#4 v h 2 1
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