View source: R/small_helpers.R
| fuse_variables | R Documentation |
When you have a situation where you have multiple variables with different NA values that happen to be in different places (where one variable has a value the other is NA and vice versa) you can fuse these together to a single variable.
fuse_variables(
data_frame,
new_variable_name,
variables_to_fuse,
drop_original_vars = TRUE
)
data_frame |
A data frame with variables to fuse. |
new_variable_name |
The name of the new fused variable. |
variables_to_fuse |
A vector with the variables that should be fused together. |
drop_original_vars |
Whether to drop or keep the original values. TRUE by default. |
Returns a data frame without the variables TYPE, TYPE_NR and DEPTH.
# Example format
sex. <- discrete_format(
"Total" = 1:2,
"Male" = 1,
"Female" = 2)
# Example data frame
my_data <- dummy_data(1000)
# Call function
all_possible <- my_data |>
summarise_plus(class = c(year, sex),
values = c(income, probability),
statistics = c("sum", "mean", "freq"),
formats = list(sex = "sex."),
weight = weight,
nesting = "all",
na.rm = TRUE)
all_possible <- all_possible[DEPTH <= 1] |>
fuse_variables("fusion", c("year", "sex"))
# NOTE: You can generally use this function to fuse variables. What is done in
# multiple steps above can be achieved by just using nested = "single" in
# summarise_plus.
single <- my_data |>
summarise_plus(class = c(year, sex),
values = c(income, probability),
statistics = c("sum", "mean", "freq"),
formats = list(sex = "sex."),
weight = weight,
nesting = "single",
na.rm = TRUE)
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