Transforming data.frame with multiple Data Column into Wide Format

Usage

poly_pivot_wider(
  data,
  id,
  param_from,
  value_from,
  labels_from = NULL,
  drop_na = TRUE,
  drop_lvl = FALSE
)

Arguments

data: (data.frame) to be pivoted.
id: (character) the name of the columns whose combination uniquely identify the observations.
param_from: (character) the name of the columns containing the names of the parameters to be pivoted. The unique values in this column will become column names in the output.
value_from: (character) the name of the column containing the values that will populate the output.
labels_from: (character) the name of the column congaing the labels of the new columns. from. If not provided, the labels will be equal to the column names. When several labels are available for the same column, the first one will be selected.
drop_na: (logical) should column containing only NAs be dropped.
drop_lvl: (logical) should missing levels be dropped in the columns coming from value_from.

Value

list of data.frame in a wide format with label attribute attached to each columns.

Details

This function is adapted to cases where the data are distributed in several columns while the name of the parameter is in one. Typical example is adsub where numeric data are stored in AVAL while categorical data are in AVALC.

Examples

test_data <- data.frame(
  the_obs = c("A", "A", "A", "B", "B", "B", "C", "D"),
  the_obs2 = c("Ax", "Ax", "Ax", "Bx", "Bx", "Bx", "Cx", "Dx"),
  the_param = c("weight", "height", "gender", "weight", "gender", "height", "height", "other"),
  the_label = c(
    "Weight (Kg)", "Height (cm)", "Gender", "Weight (Kg)",
    "Gender", "Height (cm)", "Height (cm)", "Pre-condition"
  ),
  the_val = c(65, 165, NA, 66, NA, 166, 155, NA),
  the_val2 = c(65, 165, "M", 66, "F", 166, 155, TRUE)
)

x <- poly_pivot_wider(
  test_data,
  c("the_obs", "the_obs2"),
  "the_param",
  c("the_val", "the_val2"),
  "the_label"
)
x
#> $the_val
#>   the_obs the_obs2 height weight
#> 1       A       Ax    165     65
#> 2       B       Bx    166     66
#> 3       C       Cx    155     NA
#> 4       D       Dx     NA     NA
#> 
#> $the_val2
#>   the_obs the_obs2 gender height other weight
#> 1       A       Ax      M    165  <NA>     65
#> 2       B       Bx      F    166  <NA>     66
#> 3       C       Cx   <NA>    155  <NA>   <NA>
#> 4       D       Dx   <NA>   <NA>  TRUE   <NA>
#> 
Reduce(function(u, v) merge(u, v, all = TRUE), x)
#>   the_obs the_obs2 height weight gender other
#> 1       A       Ax    165     65      M  <NA>
#> 2       B       Bx    166     66      F  <NA>
#> 3       C       Cx    155     NA   <NA>  <NA>
#> 4       D       Dx     NA     NA   <NA>  TRUE