How do I transpose a dataframe properly in R [duplicate]

Question

I am struggling with what I hope is a fairly basic problem in transposing a dataframe.

My dataframe has a structure like this:

Measure = c("Heightpercentile", "Weightpercentile", "Shoesize")
Value = c(56,60,10,45,48,7,78,60,9)
Person = c("ID4", "ID4", "ID4", "ID6", "ID6", "ID6", "ID7", "ID7", ID7")

So I have three columns and (in this example) nine rows, with three rows for each ID#.

And I would like a structure like this:

Person= c("ID4", "ID6", "ID7")
Heightpercentile = c(56,45,78)
Weightpercentile = c(60,47,60)
Shoesize = (10,7,9)

So four columns and three rows, with one row for each ID#.

I have been trying to work with transpose and was looking at pivot from dplyr but I'm just not getting it. Thanks!

Waldi · Accepted Answer · 2024-08-22 07:06:49Z

2

You could use pivot_wider:

library(tidyr)

pivot_wider(df,names_from= "Person",values_from="Value") 


# Measure            ID4   ID6   ID7
#  <chr>            <dbl> <dbl> <dbl>
#1 Heightpercentile    56    45    78
#2 Weightpercentile    60    48    60
#3 Shoesize            10     7     9

or with data.table:

library(data.table)

setDT(df)

dcast(df,Measure~Person,value.var = "Value")

#Key: <Measure>
#            Measure   ID4   ID6   ID7
#             <char> <num> <num> <num>
#1: Heightpercentile    56    45    78
#2:         Shoesize    10     7     9
#3: Weightpercentile    60    48    60

data:

df <- data.frame(Measure = c("Heightpercentile", "Weightpercentile", "Shoesize"),
                 Value = c(56,60,10,45,48,7,78,60,9),
                 Person = c("ID4", "ID4", "ID4", "ID6", "ID6", "ID6", "ID7", "ID7", "ID7"))

edited Aug 22, 2024 at 7:06

answered Aug 22, 2024 at 5:04

Waldi

41.6k6 gold badges38 silver badges90 bronze badges

Sign up to request clarification or add additional context in comments.

Collectives™ on Stack Overflow

How do I transpose a dataframe properly in R [duplicate]

1 Answer 1

Comments

Linked

Hot Network Questions

Collectives™ on Stack Overflow

1 Answer 1

Comments

Linked

Related