CODEWITHSUNDEEP
rdataframe
Lucas Lazari
Lucas Lazari

Reputation: 119

Make column values as column names in R

So I have this dataframe:

      mass        value
1 2390.421 0.0001376894
2 2390.713 0.0001362054
3 2391.004 0.0001346138
4 2391.296 0.0001329289
5 2391.588 0.0001311646
6 2391.879 0.0001293351

What I need is that the mass values becomes the column names:

   2390.421      2390.713       2391.004  ..... 
0.0001376894   0.0001362054   0.0001346138 .....

I tried reshape, unstack, do.call, but I still couldn't do it.

What can I do?

Upvotes: 0

Views: 731

Answers (3)

ThomasIsCoding
ThomasIsCoding

Reputation: 102880

A base R option

> t(unstack(rev(df)))
        2390.421     2390.713     2391.004     2391.296     2391.588
res 0.0001376894 0.0001362054 0.0001346138 0.0001329289 0.0001311646
        2391.879
res 0.0001293351

or a data.table option

> dcast(setDT(df), . ~ mass, value = "value")[, -1]
       2390.421     2390.713     2391.004     2391.296     2391.588
1: 0.0001376894 0.0001362054 0.0001346138 0.0001329289 0.0001311646
       2391.879
1: 0.0001293351

Data

> dput(df)
structure(list(mass = c(2390.421, 2390.713, 2391.004, 2391.296,
2391.588, 2391.879), value = c(0.0001376894, 0.0001362054, 0.0001346138,
0.0001329289, 0.0001311646, 0.0001293351)), class = "data.frame", row.names = c("1",
"2", "3", "4", "5", "6"))

Upvotes: 1

akrun
akrun

Reputation: 887951

We can use transpose from data.table

data.table::transpose(df1, make.names = 'mass')
#    2390.421     2390.713     2391.004     2391.296     2391.588     2391.879
#1 0.0001376894 0.0001362054 0.0001346138 0.0001329289 0.0001311646 0.0001293351

Or with deframe/as_tibble_row

library(tibble)
library(dplyr)
deframe(df1) %>%
   as_tibble_row
# A tibble: 1 x 6
#  `2390.421` `2390.713` `2391.004` `2391.296` `2391.588` `2391.879`
#       <dbl>      <dbl>      <dbl>      <dbl>      <dbl>      <dbl>
#1   0.000138   0.000136   0.000135   0.000133   0.000131   0.000129

Or using xtabs from base R

xtabs(value ~ mass, df1)
#mass
#    2390.421     2390.713     2391.004     2391.296     2391.588     2391.879 
#0.0001376894 0.0001362054 0.0001346138 0.0001329289 0.0001311646 0.0001293351

It is a matrix, but can be converted to data.frame

as.data.frame.list(xtabs(value ~ mass, df1) , check.names = FALSE)
#   2390.421     2390.713     2391.004     2391.296     2391.588     2391.879
#1 0.0001376894 0.0001362054 0.0001346138 0.0001329289 0.0001311646 0.0001293351

data

df1 <- structure(list(mass = c(2390.421, 2390.713, 2391.004, 2391.296, 
2391.588, 2391.879), value = c(0.0001376894, 0.0001362054, 0.0001346138, 
0.0001329289, 0.0001311646, 0.0001293351)), class = "data.frame",
row.names = c("1", 
"2", "3", "4", "5", "6"))

Upvotes: 2

latlio
latlio

Reputation: 1587

What about a dplyr solution:

library(tidyverse)
df1 %>% pivot_wider(names_from = a, values_from = b)

# A tibble: 1 x 6
  `2390.421` `2390.713` `2391.004` `2391.296` `2391.588` `2391.879`
       <dbl>      <dbl>      <dbl>      <dbl>      <dbl>      <dbl>
1   0.000138   0.000136   0.000135   0.000133   0.000131   0.000129

Upvotes: 4

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