How to use pivot_longer() in R to separate columns into multiple rows by category?

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Here is some fictional data:

tibble(fruit = rep(c("apple", "pear", "orange"), each = 3),
       size = rep(c("big", "medium", "small"), times = 3),
       # summer stock
       shopA_summer_wk1 = abs(round(rnorm(9, 10, 5), 0)),
       shopA_summer_wk2 = abs(round(rnorm(9, 10, 5), 0)),
       shopB_summer_wk1 = abs(round(rnorm(9, 10, 5), 0)),
       shopB_summer_wk2 = abs(round(rnorm(9, 10, 5), 0)),
       shopC_summer_wk1 = abs(round(rnorm(9, 10, 5), 0)),
       shopC_summer_wk2 = abs(round(rnorm(9, 10, 5), 0)),
       # winter stock
       shopA_winter_wk1 = abs(round(rnorm(9, 8, 4), 0)),
       shopA_winter_wk2 = abs(round(rnorm(9, 8, 4), 0)),
       shopA_winter_wk3 = abs(round(rnorm(9, 8, 4), 0)),
       shopB_winter_wk1 = abs(round(rnorm(9, 8, 4), 0)),
       shopB_winter_wk2 = abs(round(rnorm(9, 8, 4), 0)),
       shopB_winter_wk3 = abs(round(rnorm(9, 8, 4), 0)),
       shopC_winter_wk1 = abs(round(rnorm(9, 8, 4), 0)),
       shopC_winter_wk2 = abs(round(rnorm(9, 8, 4), 0)),
       shopC_winter_wk3 = abs(round(rnorm(9, 8, 4), 0)))

Some data is collected for 3 shops (A, B, C) across 2 weeks in the summer and 3 weeks in the winter. The data collected is the number of fruits (apple, pear, orange) per size (big, medium, small) the shop had in stock on that particular week.

Here are the first 6 rows of of the dataset:

# fruit  size   shopA_summer_wk1   shopA_summer_wk2 shopB_summer_wk1 shopB_summer_wk2 shopC_summer_wk1 shopC_summer_wk2 shopA_winter_wk1 shopA_winter_wk2 shopA_winter_wk3
#   <chr>  <chr>             <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>            <dbl>
# 1 apple  big                   9               12               12               16               15                5               14                4                0
# 2 apple  medium               21               16               16                1               12               11                8                8                9
# 3 apple  small                10                6               18               18               22               12                4                2                0
# 4 pear   big                  13                7                4               12               13                6               10                6                2
# 5 pear   medium               13               12                8                0                8                5               11                7                3
# 6 pear   small                16               18                4                3               13                8                7                5                0

I would like to use the pivot_longer() function in R to restructure this dataset. Given that there are quite a few group categories I'm having difficulty in writing the code for this.

I would like it to look something like the following:

fruit_dataset_long

I would greatly appreciate any input :)

tidyr reshape dataframe pivot r
2 Answers

Using the names_pattern argument, we can do:

pivot_longer(df, c(-fruit, -size), names_pattern = '(^.*)_wk(.*$)',
              names_to = c('Shop_season', 'week'))
#> # A tibble: 135 x 5
#>    fruit size  Shop_season  week  value
#>    <chr> <chr> <chr>        <chr> <dbl>
#>  1 apple big   shopA_summer 1        11
#>  2 apple big   shopA_summer 2         8
#>  3 apple big   shopB_summer 1         4
#>  4 apple big   shopB_summer 2        24
#>  5 apple big   shopC_summer 1         9
#>  6 apple big   shopC_summer 2        10
#>  7 apple big   shopA_winter 1         9
#>  8 apple big   shopA_winter 2        12
#>  9 apple big   shopA_winter 3         5
#> 10 apple big   shopB_winter 1         5
#> # ... with 125 more rows

You might also want to separate shop and season, since these are really two different variables:

pivot_longer(df, c(-fruit, -size), names_pattern = '(^.*)_wk(.*$)',
              names_to = c('Shop_season', 'week')) %>%
   separate(Shop_season, into = c('shop', 'season'))
#> # A tibble: 135 x 6
#>    fruit size  shop  season week  value
#>    <chr> <chr> <chr> <chr>  <chr> <dbl>
#>  1 apple big   shopA summer 1        11
#>  2 apple big   shopA summer 2         8
#>  3 apple big   shopB summer 1         4
#>  4 apple big   shopB summer 2        24
#>  5 apple big   shopC summer 1         9
#>  6 apple big   shopC summer 2        10
#>  7 apple big   shopA winter 1         9
#>  8 apple big   shopA winter 2        12
#>  9 apple big   shopA winter 3         5
#> 10 apple big   shopB winter 1         5
#> #... with 125 more rows
user_125003150

If data is dt, then

pivot_longer(
  data = dt,
  cols = -c(fruit:size),
  names_to = c("shop_season", "week"),
  names_pattern = "(.*)_(.*)"
)

Output:

# A tibble: 135 x 5
   fruit size  shop_season  week  value
   <chr> <chr> <chr>        <chr> <dbl>
 1 apple big   shopA_summer wk1      13
 2 apple big   shopA_summer wk2      12
 3 apple big   shopB_summer wk1       9
 4 apple big   shopB_summer wk2       9
 5 apple big   shopC_summer wk1       7
 6 apple big   shopC_summer wk2      17
 7 apple big   shopA_winter wk1      10
 8 apple big   shopA_winter wk2      17
 9 apple big   shopA_winter wk3      12
10 apple big   shopB_winter wk1       8
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