Reputation: 449
Hi all I have got a dataframe. I need to create another column so that it should tell at what place each categories are there. For example PLease refer expected output
df
ColB ColA
X A>B>C
U B>C>A
Z C>A>B
Expected output
df1
ColB ColA A B C
X A>B>C 1 2 3
U B>C>A 3 1 2
Z C>A>B 2 3 1
Upvotes: 0
Views: 26
Reputation: 887048
We can do this in base R
df[LETTERS[1:3]] <- t(sapply(regmatches(df$ColA, gregexpr("[A-Z]",
df$ColA)), match, x = LETTERS[1:3]))
df
# ColB ColA A B C
#1 X A>B>C 1 2 3
#2 U B>C>A 3 1 2
#3 Z C>A>B 2 3 1
df <- structure(list(ColB = structure(c(2L, 1L, 3L), .Label = c("U",
"X", "Z"), class = "factor"), ColA = structure(1:3, .Label = c("A>B>C",
"B>C>A", "C>A>B"), class = "factor")), class = "data.frame",
row.names = c(NA,
-3L))
Upvotes: 0
Reputation: 388907
We can first bring ColA
into separate rows, group_by
ColB
and give an unique row number for each entry and then convert the data into wide format using pivot_wider
.
library(dplyr)
library(tidyr)
df %>%
mutate(ColC = ColA) %>%
separate_rows(ColC, sep = ">") %>%
group_by(ColB) %>%
mutate(row = row_number()) %>%
pivot_wider(names_from = ColC, values_from = row)
# ColB ColA A B C
# <fct> <fct> <int> <int> <int>
#1 X A>B>C 1 2 3
#2 U B>C>A 3 1 2
#3 Z C>A>B 2 3 1
data
df <- structure(list(ColB = structure(c(2L, 1L, 3L), .Label = c("U",
"X", "Z"), class = "factor"), ColA = structure(1:3, .Label = c("A>B>C",
"B>C>A", "C>A>B"), class = "factor")), class = "data.frame", row.names = c(NA, -3L))
Upvotes: 1