I have a dataframe as below, I want to create dummy columns based for each unique string available in the genres column
tconst genres
1: tt0000001 Documentary,Short
2: tt0000002 Animation,Short
3: tt0000003 Animation,Comedy,Romance
4: tt0000004 Animation,Short
5: tt0000005 Comedy,Short
6: tt0000006 Short
7: tt0000007 Short,Sport
8: tt0000008 Documentary,Short
9: tt0000009 Romance,Short
10: tt0000010 Documentary,Short
11: tt0000011 Documentary,Short
12: tt0000012 Documentary,Short
13: tt0000013 Documentary,Short
14: tt0000014 Comedy,Short
15: tt0000015 Animation,Short
I have tried to use the code below, apart from not being efficient, it is returning incorrect output.
uniqueGenre <- MovieRating_test %>%
separate_rows(genres) %>%
pull() %>%
unique()
for(i in 1:nrow(MovieRating_test)){
for(j in uniqueGenre){
MovieRating_test[i,j] <- ifelse(j %in% strsplit(as.character(MovieRating_test[,"genres"][i]),","), 1, 0)
}
}
dataset
MovieRating_test <- structure(list(tconst = c("tt0000001", "tt0000002", "tt0000003",
"tt0000004", "tt0000005", "tt0000006", "tt0000007", "tt0000008",
"tt0000009", "tt0000010", "tt0000011", "tt0000012", "tt0000013",
"tt0000014", "tt0000015"), genres = c("Documentary,Short", "Animation,Short",
"Animation,Comedy,Romance", "Animation,Short", "Comedy,Short",
"Short", "Short,Sport", "Documentary,Short", "Romance,Short",
"Documentary,Short", "Documentary,Short", "Documentary,Short",
"Documentary,Short", "Comedy,Short", "Animation,Short")), row.names = c(NA,
-15L), class = c("data.table", "data.frame"), .internal.selfref = <pointer: 0x0000023514d61ef0>)
a data.table solution would be prefered but any solution is welcome.
>Solution :
We may use dummy_cols from fastDummies
library(fastDummies)
dummy_cols(MovieRating_test, 'genres', split = ",")
-output
tconst genres genres_Animation genres_Comedy genres_Romance genres_Short genres_Documentary
<char> <char> <int> <int> <int> <int> <int>
1: tt0000001 Documentary,Short 0 0 0 1 1
2: tt0000002 Animation,Short 1 0 0 1 0
3: tt0000003 Animation,Comedy,Romance 1 1 1 0 0
4: tt0000004 Animation,Short 1 0 0 1 0
5: tt0000005 Comedy,Short 0 1 0 1 0
6: tt0000006 Short 0 0 0 1 0
7: tt0000007 Short,Sport 0 0 0 1 0
8: tt0000008 Documentary,Short 0 0 0 1 1
9: tt0000009 Romance,Short 0 0 1 1 0
10: tt0000010 Documentary,Short 0 0 0 1 1
11: tt0000011 Documentary,Short 0 0 0 1 1
12: tt0000012 Documentary,Short 0 0 0 1 1
13: tt0000013 Documentary,Short 0 0 0 1 1
14: tt0000014 Comedy,Short 0 1 0 1 0
15: tt0000015 Animation,Short 1 0 0 1 0
genres_Sport
<int>
1: 0
2: 0
3: 0
4: 0
5: 0
6: 0
7: 1
8: 0
9: 0
10: 0
11: 0
12: 0
13: 0
14: 0
15: 0
Or another option with mtabulate
library(data.table)
library(qdapTools)
m1 <- MovieRating_test[, +(mtabulate(strsplit(genres, ",")) > 0)]
MovieRating_test[, colnames(m1) := as.data.frame(m1)]
-output
> MovieRating_test
tconst genres Animation Comedy Documentary Romance Short Sport
<char> <char> <int> <int> <int> <int> <int> <int>
1: tt0000001 Documentary,Short 0 0 1 0 1 0
2: tt0000002 Animation,Short 1 0 0 0 1 0
3: tt0000003 Animation,Comedy,Romance 1 1 0 1 0 0
4: tt0000004 Animation,Short 1 0 0 0 1 0
5: tt0000005 Comedy,Short 0 1 0 0 1 0
6: tt0000006 Short 0 0 0 0 1 0
7: tt0000007 Short,Sport 0 0 0 0 1 1
8: tt0000008 Documentary,Short 0 0 1 0 1 0
9: tt0000009 Romance,Short 0 0 0 1 1 0
10: tt0000010 Documentary,Short 0 0 1 0 1 0
11: tt0000011 Documentary,Short 0 0 1 0 1 0
12: tt0000012 Documentary,Short 0 0 1 0 1 0
13: tt0000013 Documentary,Short 0 0 1 0 1 0
14: tt0000014 Comedy,Short 0 1 0 0 1 0
15: tt0000015 Animation,Short 1 0 0 0 1 0