mirror of
https://github.com/agdamsbo/FreesearchR.git
synced 2026-06-19 04:27:30 +02:00
157 lines
5 KiB
Markdown
157 lines
5 KiB
Markdown
# Alternative pivoting method for easily pivoting based on name pattern
|
|
|
|
This function requires and assumes a systematic naming of variables. For
|
|
now only supports one level pivoting. Adding more levels would require
|
|
an added "ignore" string pattern or similarly. Example 2.
|
|
|
|
## Usage
|
|
|
|
``` r
|
|
wide2long(
|
|
data,
|
|
pattern,
|
|
type = c("prefix", "infix", "suffix"),
|
|
id.col = 1,
|
|
instance.name = "instance"
|
|
)
|
|
```
|
|
|
|
## Arguments
|
|
|
|
- data:
|
|
|
|
data
|
|
|
|
- pattern:
|
|
|
|
pattern(s) to match. Character vector of length 1 or more.
|
|
|
|
- type:
|
|
|
|
type of match. can be one of "prefix","infix" or "suffix".
|
|
|
|
- id.col:
|
|
|
|
ID column. Will fill ID for all. Column name or numeric index. Default
|
|
is "1", first column.
|
|
|
|
- instance.name:
|
|
|
|
## Value
|
|
|
|
data.frame
|
|
|
|
## Examples
|
|
|
|
``` r
|
|
data.frame(
|
|
1:20, sample(70:80, 20, TRUE),
|
|
sample(70:100, 20, TRUE),
|
|
sample(70:100, 20, TRUE),
|
|
sample(170:200, 20, TRUE)
|
|
) |>
|
|
setNames(c("id", "age", "weight_0", "weight_1", "height_1")) |>
|
|
wide2long(pattern = c("_0", "_1"), type = "suffix")
|
|
#> id age instance weight height
|
|
#> 1 1 74 0 98 NA
|
|
#> 2 1 NA 1 91 173
|
|
#> 3 2 78 0 77 NA
|
|
#> 4 2 NA 1 91 189
|
|
#> 5 3 78 0 80 NA
|
|
#> 6 3 NA 1 73 184
|
|
#> 7 4 70 0 88 NA
|
|
#> 8 4 NA 1 95 199
|
|
#> 9 5 72 0 85 NA
|
|
#> 10 5 NA 1 83 179
|
|
#> 11 6 73 0 90 NA
|
|
#> 12 6 NA 1 75 192
|
|
#> 13 7 71 0 85 NA
|
|
#> 14 7 NA 1 78 195
|
|
#> 15 8 78 0 83 NA
|
|
#> 16 8 NA 1 99 198
|
|
#> 17 9 80 0 85 NA
|
|
#> 18 9 NA 1 70 175
|
|
#> 19 10 77 0 74 NA
|
|
#> 20 10 NA 1 79 186
|
|
#> 21 11 76 0 92 NA
|
|
#> 22 11 NA 1 80 193
|
|
#> 23 12 73 0 71 NA
|
|
#> 24 12 NA 1 84 194
|
|
#> 25 13 77 0 94 NA
|
|
#> 26 13 NA 1 72 198
|
|
#> 27 14 75 0 96 NA
|
|
#> 28 14 NA 1 89 183
|
|
#> 29 15 79 0 77 NA
|
|
#> 30 15 NA 1 94 178
|
|
#> 31 16 75 0 99 NA
|
|
#> 32 16 NA 1 73 189
|
|
#> 33 17 73 0 99 NA
|
|
#> 34 17 NA 1 75 185
|
|
#> 35 18 72 0 70 NA
|
|
#> 36 18 NA 1 83 172
|
|
#> 37 19 80 0 70 NA
|
|
#> 38 19 NA 1 79 172
|
|
#> 39 20 74 0 89 NA
|
|
#> 40 20 NA 1 97 179
|
|
data.frame(
|
|
1:20, sample(70:80, 20, TRUE),
|
|
sample(70:100, 20, TRUE),
|
|
sample(70:100, 20, TRUE),
|
|
sample(170:200, 20, TRUE)
|
|
) |>
|
|
setNames(c("id", "age", "weight_0", "weight_a_1", "height_b_1")) |>
|
|
wide2long(pattern = c("_0", "_1"), type = "suffix")
|
|
#> id age instance weight weight_a height_b
|
|
#> 1 1 77 0 83 NA NA
|
|
#> 2 1 NA 1 NA 97 197
|
|
#> 3 2 78 0 79 NA NA
|
|
#> 4 2 NA 1 NA 94 186
|
|
#> 5 3 79 0 77 NA NA
|
|
#> 6 3 NA 1 NA 77 200
|
|
#> 7 4 76 0 88 NA NA
|
|
#> 8 4 NA 1 NA 100 181
|
|
#> 9 5 74 0 95 NA NA
|
|
#> 10 5 NA 1 NA 73 175
|
|
#> 11 6 70 0 99 NA NA
|
|
#> 12 6 NA 1 NA 83 185
|
|
#> 13 7 72 0 71 NA NA
|
|
#> 14 7 NA 1 NA 84 174
|
|
#> 15 8 70 0 77 NA NA
|
|
#> 16 8 NA 1 NA 94 184
|
|
#> 17 9 80 0 70 NA NA
|
|
#> 18 9 NA 1 NA 93 195
|
|
#> 19 10 79 0 77 NA NA
|
|
#> 20 10 NA 1 NA 77 187
|
|
#> 21 11 72 0 77 NA NA
|
|
#> 22 11 NA 1 NA 76 177
|
|
#> 23 12 77 0 75 NA NA
|
|
#> 24 12 NA 1 NA 80 170
|
|
#> 25 13 73 0 99 NA NA
|
|
#> 26 13 NA 1 NA 81 172
|
|
#> 27 14 70 0 74 NA NA
|
|
#> 28 14 NA 1 NA 98 189
|
|
#> 29 15 71 0 98 NA NA
|
|
#> 30 15 NA 1 NA 98 184
|
|
#> 31 16 74 0 73 NA NA
|
|
#> 32 16 NA 1 NA 78 173
|
|
#> 33 17 71 0 100 NA NA
|
|
#> 34 17 NA 1 NA 79 172
|
|
#> 35 18 80 0 74 NA NA
|
|
#> 36 18 NA 1 NA 77 181
|
|
#> 37 19 72 0 98 NA NA
|
|
#> 38 19 NA 1 NA 89 176
|
|
#> 39 20 72 0 85 NA NA
|
|
#> 40 20 NA 1 NA 81 174
|
|
# Optional filling of missing values by last observation carried forward
|
|
# Needed for mmrm analyses
|
|
long_missings |>
|
|
# Fills record ID assuming none are missing
|
|
tidyr::fill(record_id) |>
|
|
# Grouping by ID for the last step
|
|
dplyr::group_by(record_id) |>
|
|
# Filling missing data by ID
|
|
tidyr::fill(names(long_missings)[!names(long_missings) %in% new_names]) |>
|
|
# Remove grouping
|
|
dplyr::ungroup()
|
|
#> Error: object 'long_missings' not found
|
|
```
|