dataframe - Pivot wider in R with 2 variables to names_from - Stack Overflow

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I have data frame in R called data:

data
# A tibble: 192 × 4
    Year Category Favor    Percentage
   <dbl> <chr>    <chr>         <dbl>
 1  2002 A        Good           35.8
 2  2002 A        Mediocre       31.9
 3  2002 A        Bad            45.3
 4  2002 B        Good           51.3
 5  2002 B        Mediocre       42.3
 6  2002 B        Bad            26.4
 7  2002 C        Good           64.4
 8  2002 C        Mediocre       33.4
 9  2002 C        Bad            24.2
10  2002 D        Good           56.2

I want to pivot wider it in order to be like ideally like the following :

category	Bad - 1998	Bad - 1999	...	Bad - 2002	Medriocre - 1998	...	Medriocre -2002	Good - 1998 ...Good - 2002
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P

I have data frame in R called data:

data
# A tibble: 192 × 4
    Year Category Favor    Percentage
   <dbl> <chr>    <chr>         <dbl>
 1  2002 A        Good           35.8
 2  2002 A        Mediocre       31.9
 3  2002 A        Bad            45.3
 4  2002 B        Good           51.3
 5  2002 B        Mediocre       42.3
 6  2002 B        Bad            26.4
 7  2002 C        Good           64.4
 8  2002 C        Mediocre       33.4
 9  2002 C        Bad            24.2
10  2002 D        Good           56.2

I want to pivot wider it in order to be like ideally like the following :

category	Bad - 1998	Bad - 1999	...	Bad - 2002	Medriocre - 1998	...	Medriocre -2002	Good - 1998 ...Good - 2002
A
B
C
D
E
F
G
H
I
J
K
L
M
N
O
P

i.e the Category column to be the first column and then starting from second Bad and 1998 third column Bad- 1999, fourth Bad- 2001,fifth Bad- 2002, sixth Medriocre - 1998,Medriocre - 1999,Medriocre - 2001,Medriocre - 2002,Good - 1998,Good - 1999,Good - 2001 and finally the column Good - 2002.

How can I do it in R using tidyverse functions ?

Data

dput(data)
structure(list(Year = c(2002, 2002, 2002, 2002, 2002, 2002, 2002, 
2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 
2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 
2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 
2002, 2002, 2002, 2002, 2002, 2002, 2002, 2002, 1998, 1998, 1998, 
1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 
1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 
1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 
1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 1998, 
1998, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 
1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 
1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 
1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 1999, 
1999, 1999, 1999, 1999, 1999, 2001, 2001, 2001, 2001, 2001, 2001, 
2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 
2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 
2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 
2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001, 2001), Category = c("A", 
"A", "A", "B", "B", "B", "C", "C", "C", "D", "D", "D", "E", "E", 
"E", "F", "F", "F", "G", "G", "G", "H", "H", "H", "I", "I", "I", 
"J", "J", "J", "K", "K", "K", "L", "L", "L", "M", "M", "M", "N", 
"N", "N", "O", "O", "O", "P", "P", "P", "A", "A", "A", "B", "B", 
"B", "C", "C", "C", "D", "D", "D", "E", "E", "E", "F", "F", "F", 
"G", "G", "G", "H", "H", "H", "I", "I", "I", "J", "J", "J", "K", 
"K", "K", "L", "L", "L", "M", "M", "M", "N", "N", "N", "O", "O", 
"O", "P", "P", "P", "A", "A", "A", "B", "B", "B", "C", "C", "C", 
"D", "D", "D", "E", "E", "E", "F", "F", "F", "G", "G", "G", "H", 
"H", "H", "I", "I", "I", "J", "J", "J", "K", "K", "K", "L", "L", 
"L", "M", "M", "M", "N", "N", "N", "O", "O", "O", "P", "P", "P", 
"A", "A", "A", "B", "B", "B", "C", "C", "C", "D", "D", "D", "E", 
"E", "E", "F", "F", "F", "G", "G", "G", "H", "H", "H", "I", "I", 
"I", "J", "J", "J", "K", "K", "K", "L", "L", "L", "M", "M", "M", 
"N", "N", "N", "O", "O", "O", "P", "P", "P"), Favor = c("Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", 
"Bad", "Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", 
"Good", "Mediocre", "Bad", "Good", "Mediocre", "Bad", "Good", 
"Mediocre", "Bad"), Percentage = c(36.85, 36.88, 46.28, 60.28, 
45.3, 36.42, 70.44, 37.39, 34.17, 58.23, 48.77, 34.99, 67.53, 
33.46, 32.01, 35.96, 35.33, 62.71, 46.84, 32.92, 42.24, 83.21, 
26.67, 16.11, 65.91, 23.94, 46.15, 81.83, 23.86, 27.31, 74.32, 
35.09, 33.59, 71.91, 30.92, 28.17, 62.84, 33.06, 27.1, 63.05, 
44.81, 26.15, 76.68, 35.99, 23.33, 49.19, 34.58, 42.23, 55.21, 
35.37, 34.42, 64.48, 36.53, 33.99, 70.81, 27.1, 31.09, 51.36, 
43, 37.65, 64.57, 34.37, 29.06, 35.55, 28.44, 56.01, 56.84, 33.36, 
38.8, 79.74, 35.74, 22.52, 66.86, 29.99, 44.15, 89.57, 27.79, 
14.64, 82.49, 27.37, 27.14, 75.92, 33.39, 18.69, 69.8, 34.69, 
29.51, 75.2, 42.63, 29.17, 90.33, 36.72, 13.95, 52.73, 30, 38.27, 
68.14, 40.61, 33.25, 66.2, 33.99, 31.81, 80.38, 26.48, 21.13, 
50.5, 40.36, 37.14, 74.17, 31.78, 29.04, 44.91, 35.24, 43.85, 
69.23, 35.44, 32.33, 86.44, 24.11, 17.46, 69.69, 33.06, 40.25, 
86.37, 21.21, 21.42, 80.11, 35.57, 32.32, 77.2, 32.03, 19.77, 
72.98, 28.08, 20.94, 70.81, 29.12, 24.07, 88.14, 22.31, 16.55, 
67.49, 44.16, 32.35, 69.03, 39.45, 28.52, 71.97, 37.6, 25.43, 
79.06, 38.4, 19.55, 68.94, 37.03, 30.03, 80.74, 30.59, 30.67, 
49.07, 45.79, 47.14, 60.1, 27.55, 34.36, 88.54, 30.2, 20.26, 
59.42, 22.98, 43.61, 86.84, 16.73, 14.43, 77.42, 22.07, 22.52, 
78.85, 23.88, 17.28, 78.22, 39.57, 27.22, 80.17, 26.21, 20.63, 
94.63, 28.66, 13.71, 65.86, 31.97, 32.16)), row.names = c(NA, 
-192L), class = c("tbl_df", "tbl", "data.frame"))

• r
• dataframe
• tidyr

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1 Answer 1

Sorted by: Reset to default 6

Probably you can try

data %>%
  arrange(
    Category,
    factor(Favor, levels = c("Bad", "Mediocre", "Good")),
    Year
  ) %>%
  pivot_wider(
    names_from = c(Favor, Year),
    values_from = Percentage,
    names_sep = "-"
  )

which gives

# A tibble: 16 × 13
   Category `Bad-1998` `Bad-1999` `Bad-2001` `Bad-2002` `Mediocre-1998`
   <chr>         <dbl>      <dbl>      <dbl>      <dbl>           <dbl>
 1 A              34.4       33.2       28.5       46.3            35.4
 2 B              34.0       31.8       25.4       36.4            36.5
 3 C              31.1       21.1       19.6       34.2            27.1
 4 D              37.6       37.1       30.0       35.0            43
 5 E              29.1       29.0       30.7       32.0            34.4
 6 F              56.0       43.8       47.1       62.7            28.4
 7 G              38.8       32.3       34.4       42.2            33.4
 8 H              22.5       17.5       20.3       16.1            35.7
 9 I              44.2       40.2       43.6       46.2            30.0
10 J              14.6       21.4       14.4       27.3            27.8
11 K              27.1       32.3       22.5       33.6            27.4
12 L              18.7       19.8       17.3       28.2            33.4
13 M              29.5       20.9       27.2       27.1            34.7
14 N              29.2       24.1       20.6       26.2            42.6
15 O              14.0       16.6       13.7       23.3            36.7
16 P              38.3       32.4       32.2       42.2            30
# ℹ 7 more variables: `Mediocre-1999` <dbl>, `Mediocre-2001` <dbl>,
#   `Mediocre-2002` <dbl>, `Good-1998` <dbl>, `Good-1999` <dbl>,
#   `Good-2001` <dbl>, `Good-2002` <dbl>

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