CODEWITHSUNDEEP
r
Paul Ibrahim
Paul Ibrahim

Reputation: 433

How do I do custom stacking in R?

I have two columns of data (as given in the code below), and I don't know how to stack them into one column in a customized order. To be clear, I want a single column (call it x) as my dataset, with entries 1-5 of column "attr" as entries 1-5 of column x, followed by entries 6-10 of column "type" as entries 6-10 in column x, followed entries 6-10 of column "attr" as entries 11-15 in column x, followed finally by entries 6-10 of column "type" as entries 16-20 in column x. My dataset is below:

analysis <- data.frame(attr = c('player_a', 'player_b', 'player_c', 'player_d', 'player_e',
                                'player_f', 'player_g', 'player_h', 'player_i', 'player_j'),
                       type = c('player_q', 'player_r', 'player_s', 'player_t', 'player_u',
                                'player_v', 'player_w', 'player_x', 'player_y', 'player_z'))

I am fairly new to R, so I apologize if I used incorrect terminology. Any help is greatly appreciated

To clarify, my desired order is:

player_a
player_b
player_c
player_d
player_e
player_q
player_r
player_s
player_t
player_u
player_f
player_g
player_h
player_i
player_j
player_v
player_w
player_x
player_y
player_z

Upvotes: 1

Views: 49

Answers (2)

see24
see24

Reputation: 1220

Here is my answer which uses the dplyr package but I'm sure you could use the same logic with data.table or base 

library(dplyr)
library(tidyr)
analysis <- data.frame(attr = c('player_a', 'player_b', 'player_c',
                                'player_d', 'player_e', 'player1', 'player2',
                                'player3', 'player4', 'player5'), 
                       type=c('player_v','player_w','player_x',
                              'player_y', 'player_z','player6', 'player7',
                              'player8', 'player9', 'player10'))
a2 <- mutate(analysis, order = c(rep(1,5),rep(2,5)))
a3 <- gather(a2, "variable", "value", -order) %>% arrange(order)

Upvotes: 0

moooh
moooh

Reputation: 469

Is this what you are looking for (uses data.table package)?

library(data.table)

analysis <- data.table(attr = c('player_a', 'player_b', 'player_c', 'player_d', 'player_e'), type=c('player_v','player_w','player_x', 'player_y', 'player_z'))

melt(analysis,measure.vars = 1:2)

    variable    value
 1:     attr player_a
 2:     attr player_b
 3:     attr player_c
 4:     attr player_d
 5:     attr player_e
 6:     type player_v
 7:     type player_w
 8:     type player_x
 9:     type player_y
10:     type player_z

Upvotes: 1

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