CODEWITHSUNDEEP
rtranspose
user2728024
user2728024

Reputation: 1556

Converting rows to columns in R

I have a data like this

id , name , age, sex
1, sam, 22, m
2, rita, 34, f
3, robin, 32, f
4, josh, 21, m

i want to convert the data to

id, name, age, m, f
1, sam, 22, 1,0
2, rita, 34, 0,1
3, robin, 32, 0,1
4, josh, 21, 1,0

Can i do this in R

other than using 

dataset$m <- with(dataset, ifelse ((Type == "m"), 1, 0))

Upvotes: 1

Views: 1367

Answers (1)

akrun
akrun

Reputation: 887851

You could try

library(reshape2)
dataset1 <- dcast(dataset, ...~sex, value.var='sex', length)
dataset1
#  id  name age f m
#1  1   sam  22 0 1
#2  2  rita  34 1 0
#3  3 robin  32 1 0
#4  4  josh  21 0 1

Update

If there are duplicate rows for 'id/name/age' columns, we could create a sequence column ('ind') and then dcast

  datasetN$ind <- with(datasetN, ave(seq_along(id), id, name,
                 age, FUN=seq_along))
  subset(dcast(datasetN, ...~sex, value.var='sex', length), 
                                    select=-ind)
  #  id  name age f m
  #1  1   sam  22 0 1
  #2  2  rita  34 1 0
  #3  3 robin  32 1 0
  #4  3 robin  32 1 0
  #5  4  josh  21 0 1

Update2

Using 'train.csv' from here

train <- read.csv('train.csv')
train$ind <- with(train, ave(seq_along(City), City, FUN=seq_along))
res <- subset(dcast(train, ...~City, value.var='City', length),
       select=-ind)
dim(res)
#[1] 137  76

data

dataset <- structure(list(id = 1:4, name = c("sam", "rita", "robin",
"josh"
), age = c(22L, 34L, 32L, 21L), sex = c("m", "f", "f", "m")),
.Names = c("id", 
"name", "age", "sex"), row.names = c(NA, -4L), class = "data.frame")

datasetN <- structure(list(id = c(1, 2, 3, 4, 3), name = c("sam", 
"rita", 
"robin", "josh", "robin"), age = c(22, 34, 32, 21, 32), sex = c("m",
"f", "f", "m", "f")), .Names = c("id", "name", "age", "sex"), 
 row.names = c(NA, 5L), class = "data.frame")

Upvotes: 2

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