for a text mining project I have to investigate the developement of a word list over time. For this, I need to split the rownames so that I have one column with the company name and one column with the year. This is a extract from my data frame:
abs access allow analysis application approach base big business challenge company
Adidas_2010.txt 13 25 26 11 41 132 1 266 13 115 1
Adidas_2011.txt 1 3 1 0 0 8 0 11 2 10 0
Adidas_2012.txt 29 35 37 22 110 181 7 384 31 136 3
Adidas_2013.txt 28 47 38 32 180 184 4 451 30 129 3
Adidas_2014.txt 12 42 38 27 159 207 6 921 32 128 6
Adidas_2016.txt 30 47 50 47 162 251 9 1061 32 171 13
Nike_2009.txt 16 15 17 12 33 177 9 346 93 196 1
Nike_2011.txt 10 30 0 3 0 0 0 81 7 31 0
Nike_2012.txt 21 22 12 57 199 300 7 214 11 107 3
Nike_2013.txt 20 32 30 11 123 321 4 331 90 239 3
Nike_2014.txt 33 43 30 33 119 137 6 441 67 318 6
Nike_2015.txt 51 42 41 27 102 151 9 1061 32 221 13
An this is my code:
dtm <- DocumentTermMatrix(corpus, control=list(dictionary = word_list))
df1 <- data.frame(as.matrix(dtm), row.names = filenames_annualreports)
I've tried this:
names_plus_year <- rownames(df1)
names_plus_year_split <- strsplit(names_plus_year, "_")
rownames(df1) <- sapply(names_plus_year_split, "[", 1)
But I receive following error:
Error in `.rowNamesDF<-`(x, value = value) :
double 'row.names' not allowed
Is there another way to split the rownames? Thanks a lot! :)
You can split the rownames, bind them rowwise and then bind them columnwise to your data frame, i.e.
cbind.data.frame(df, do.call(rbind, strsplit(sub('\\..*','' ,rownames(df)), '_')))
which gives,
abs access allow analysis application approach base big business challenge company 1 2 Adidas_2010.txt 13 25 26 11 41 132 1 266 13 115 1 Adidas 2010 Adidas_2011.txt 1 3 1 0 0 8 0 11 2 10 0 Adidas 2011 Adidas_2012.txt 29 35 37 22 110 181 7 384 31 136 3 Adidas 2012 Adidas_2013.txt 28 47 38 32 180 184 4 451 30 129 3 Adidas 2013 Adidas_2014.txt 12 42 38 27 159 207 6 921 32 128 6 Adidas 2014 Adidas_2016.txt 30 47 50 47 162 251 9 1061 32 171 13 Adidas 2016 Nike_2009.txt 16 15 17 12 33 177 9 346 93 196 1 Nike 2009 Nike_2011.txt 10 30 0 3 0 0 0 81 7 31 0 Nike 2011 Nike_2012.txt 21 22 12 57 199 300 7 214 11 107 3 Nike 2012 Nike_2013.txt 20 32 30 11 123 321 4 331 90 239 3 Nike 2013 Nike_2014.txt 33 43 30 33 119 137 6 441 67 318 6 Nike 2014 Nike_2015.txt 51 42 41 27 102 151 9 1061 32 221 13 Nike 2015
You can change the names as per usual.
DATA
dput(df)
structure(list(abs = c(13L, 1L, 29L, 28L, 12L, 30L, 16L, 10L,
21L, 20L, 33L, 51L), access = c(25L, 3L, 35L, 47L, 42L, 47L,
15L, 30L, 22L, 32L, 43L, 42L), allow = c(26L, 1L, 37L, 38L, 38L,
50L, 17L, 0L, 12L, 30L, 30L, 41L), analysis = c(11L, 0L, 22L,
32L, 27L, 47L, 12L, 3L, 57L, 11L, 33L, 27L), application = c(41L,
0L, 110L, 180L, 159L, 162L, 33L, 0L, 199L, 123L, 119L, 102L),
approach = c(132L, 8L, 181L, 184L, 207L, 251L, 177L, 0L,
300L, 321L, 137L, 151L), base = c(1L, 0L, 7L, 4L, 6L, 9L,
9L, 0L, 7L, 4L, 6L, 9L), big = c(266L, 11L, 384L, 451L, 921L,
1061L, 346L, 81L, 214L, 331L, 441L, 1061L), business = c(13L,
2L, 31L, 30L, 32L, 32L, 93L, 7L, 11L, 90L, 67L, 32L), challenge = c(115L,
10L, 136L, 129L, 128L, 171L, 196L, 31L, 107L, 239L, 318L,
221L), company = c(1L, 0L, 3L, 3L, 6L, 13L, 1L, 0L, 3L, 3L,
6L, 13L)), row.names = c("Adidas_2010.txt", "Adidas_2011.txt",
"Adidas_2012.txt", "Adidas_2013.txt", "Adidas_2014.txt", "Adidas_2016.txt",
"Nike_2009.txt", "Nike_2011.txt", "Nike_2012.txt", "Nike_2013.txt",
"Nike_2014.txt", "Nike_2015.txt"), class = "data.frame")