CODEWITHSUNDEEP
r
Andrew
Andrew

Reputation: 23

Convert binary data frame to string

I have an R data frame with movies from IMDB.

(Here is the CSV file: http://had.co.nz/data/movies/movies.tab.gz)

Genres are defined by the binary table:

$ Action      (int) 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 1,...
$ Animation   (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
$ Comedy      (int) 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1,...
$ Drama       (int) 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 0,...
$ Documentary (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,...
$ Romance     (int) 1, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0,...
$ Short       (int) 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0,...

I am wondering: is there an elegant, R-native way to convert this binary table into the string like “Comedy, Romance” in the same data frame?

Thank you in advance for your help!

Upvotes: 2

Views: 492

Answers (3)

Anders Ellern Bilgrau
Anders Ellern Bilgrau

Reputation: 10223

I think this is what you want.

# Create some toy data like yours
set.seed(1)
n <- 5
ds <- as.data.frame(replicate(7, sample(0:1, n, replace = TRUE)))
names(ds) <- c("Action", "Animation", "Comedy", "Drama",
                "Documentary", "Romance", "Short")
print(ds)
#  Action Animation Comedy Drama Documentary Romance Short
#1      0         1      0     0           1       0     0
#2      0         1      0     1           0       0     1
#3      1         1      1     1           1       0     0
#4      1         1      0     0           0       1     0
#5      0         0      1     1           0       0     1

# Use each row as indicator vector
apply(ds, 1, function(r) paste(names(ds)[as.logical(r)], collapse = ", "))
#[1] "Animation, Documentary"                       
#[2] "Animation, Drama, Short"                      
#[3] "Action, Animation, Comedy, Drama, Documentary"
#[4] "Action, Animation, Romance"                   
#[5] "Comedy, Drama, Short"

Upvotes: 2

lukeA
lukeA

Reputation: 54237

I'd also opt for data.table:

library(readr)
library(data.table)
dt <- read_tsv("http://had.co.nz/data/movies/movies.tab.gz")
dt <- setkey(melt(setDT(dt), id.vars=1:17)[value==1], "title")
(dt <- unique(dt[dt[, .(categories=list(variable)), by=title]][, c("variable", "value"):=NULL]))
#                          title year length   budget rating votes   r1   r2  r3   r4   r5   r6   r7   r8   r9  r10  mpaa      categories
#     1:                       $ 1971    121       NA    6.4   348  4.5  4.5 4.5  4.5 14.5 24.5 24.5 14.5  4.5  4.5    NA    Comedy,Drama
#     2:       $1000 a Touchdown 1939     71       NA    6.0    20  0.0 14.5 4.5 24.5 14.5 14.5 14.5  4.5  4.5 14.5    NA          Comedy
#     3:  $21 a Day Once a Month 1941      7       NA    8.2     5  0.0  0.0 0.0  0.0  0.0 24.5  0.0 44.5 24.5 24.5    NA Animation,Short
#     4:                 $40,000 1996     70       NA    8.2     6 14.5  0.0 0.0  0.0  0.0  0.0  0.0  0.0 34.5 45.5    NA          Comedy
#     5:                   $pent 2000     91       NA    4.3    45  4.5  4.5 4.5 14.5 14.5 14.5  4.5  4.5 14.5 14.5    NA           Drama
#    ---                                                                                                                                 
# 44177:                  sIDney 2002     15       NA    7.0     8 14.5  0.0 0.0 14.5  0.0  0.0 24.5 14.5 14.5 24.5    NA    Action,Short
# 44178:               tom thumb 1958     98       NA    6.5   274  4.5  4.5 4.5  4.5 14.5 14.5 24.5 14.5  4.5  4.5    NA       Animation
# 44179:             www.XXX.com 2003    105       NA    1.1    12 45.5  0.0 0.0  0.0  0.0  0.0 24.5  0.0  0.0 24.5    NA   Drama,Romance
# 44180:                     xXx 2002    132 85000000    5.5 18514  4.5  4.5 4.5  4.5 14.5 14.5 14.5 14.5  4.5  4.5 PG-13          Action
# 44181: xXx: State of the Union 2005    101 87000000    3.9  1584 24.5  4.5 4.5  4.5  4.5 14.5  4.5  4.5  4.5 14.5 PG-13          Action

You may want to leave the categories columns as vectors or lists in order to be able to process it easily:

head(dt$categories, 2)
# [[1]]
# [1] Comedy Drama 
# Levels: Action Animation Comedy Drama Documentary Romance Short
# 
# [[2]]
# [1] Comedy
# Levels: Action Animation Comedy Drama Documentary Romance Short

Upvotes: 0

akrun
akrun

Reputation: 887173

Here is another option using data.table

library(data.table)
library(reshape2)
 setDT(melt(as.matrix(ds)))[value!=0][,toString(Var2) ,Var1]

Upvotes: 0

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