Create a nested data frame — make

This function is very similar to tidyr::nest()in that it creates a data frame where one of the columns is comprised of a list of data frames.

Usage

make_nested(data, group, na.rm = TRUE, sep = "_")

Arguments

data: A data frame
group: Columns to nest by; these will remain in the outer data frame. If data is not a grouped data frame, then this must be supplied. If supplying multiple must be in a vector. Can be either a string or symbol.
na.rm: Determines if rows with NA should be kept or dropped. Defaults to TRUE.
sep: A character string to separate the values. This is the sep argument in paste(). Check examples to to see it in action.

Details

While similar to tidyr::nest() there are a few key differences.

The first is that this function uses the vctrs package under the hood, which makes it about twice as fast as tidyr::nest().

Second, it is more limited in its scope and functionality. Where tidyr::nest() allows you to determine which columns are in the inner data frames (the ones in the list column), this function does not. Instead, you are only able to specify the variables that remain in the outer data frame.

Third, this function creates an extra column called "name" that concatenates the values from the columns in the outer rows together using paste().

Fourth, unlike in tidyr::nest() where variables supplied to the .by argument supersede any grouping variables specified through dplyr::group_by(), nest_data() combines the two to nest the data.

Examples


library(dplyr)
# nest by one variable
make_nested(test_data, pid_f3)
#> # A tibble: 3 × 3
#>   pid_f3      data               name       
#>   <fct>       <list>             <chr>      
#> 1 Democrat    <tibble [98 × 45]> Democrat   
#> 2 Independent <tibble [57 × 45]> Independent
#> 3 Republican  <tibble [95 × 45]> Republican 

# nest by multiple variables
make_nested(test_data, c(pid_f3, edu_f2))
#> # A tibble: 6 × 4
#>   pid_f3      edu_f2                       data               name              
#>   <fct>       <fct>                        <list>             <chr>             
#> 1 Democrat    No College Degree            <tibble [52 × 44]> Democrat_No Colle…
#> 2 Democrat    At Least a Bachelor's Degree <tibble [46 × 44]> Democrat_At Least…
#> 3 Independent No College Degree            <tibble [40 × 44]> Independent_No Co…
#> 4 Independent At Least a Bachelor's Degree <tibble [17 × 44]> Independent_At Le…
#> 5 Republican  No College Degree            <tibble [50 × 44]> Republican_No Col…
#> 6 Republican  At Least a Bachelor's Degree <tibble [45 × 44]> Republican_At Lea…

# group data to create nested data frame
test_data %>% 
  dplyr::group_by(pid_f3, edu_f2) %>% 
  make_nested()
#> # A tibble: 6 × 4
#>   pid_f3      edu_f2                       data               name              
#>   <fct>       <fct>                        <list>             <chr>             
#> 1 Democrat    No College Degree            <tibble [52 × 44]> Democrat_No Colle…
#> 2 Democrat    At Least a Bachelor's Degree <tibble [46 × 44]> Democrat_At Least…
#> 3 Independent No College Degree            <tibble [40 × 44]> Independent_No Co…
#> 4 Independent At Least a Bachelor's Degree <tibble [17 × 44]> Independent_At Le…
#> 5 Republican  No College Degree            <tibble [50 × 44]> Republican_No Col…
#> 6 Republican  At Least a Bachelor's Degree <tibble [45 × 44]> Republican_At Lea…

# use group_by and nest_data 
test_data %>% 
  dplyr::group_by(pid_f3) %>% 
  make_nested(edu_f2)
#> # A tibble: 6 × 4
#>   pid_f3      edu_f2                       data               name              
#>   <fct>       <fct>                        <list>             <chr>             
#> 1 Democrat    No College Degree            <tibble [52 × 44]> Democrat_No Colle…
#> 2 Democrat    At Least a Bachelor's Degree <tibble [46 × 44]> Democrat_At Least…
#> 3 Independent No College Degree            <tibble [40 × 44]> Independent_No Co…
#> 4 Independent At Least a Bachelor's Degree <tibble [17 × 44]> Independent_At Le…
#> 5 Republican  No College Degree            <tibble [50 × 44]> Republican_No Col…
#> 6 Republican  At Least a Bachelor's Degree <tibble [45 × 44]> Republican_At Lea…

# use different sep argument
make_nested(test_data, c(pid_f3, edu_f2), sep = ":")
#> # A tibble: 6 × 4
#>   pid_f3      edu_f2                       data               name              
#>   <fct>       <fct>                        <list>             <chr>             
#> 1 Democrat    No College Degree            <tibble [52 × 44]> Democrat:No Colle…
#> 2 Democrat    At Least a Bachelor's Degree <tibble [46 × 44]> Democrat:At Least…
#> 3 Independent No College Degree            <tibble [40 × 44]> Independent:No Co…
#> 4 Independent At Least a Bachelor's Degree <tibble [17 × 44]> Independent:At Le…
#> 5 Republican  No College Degree            <tibble [50 × 44]> Republican:No Col…
#> 6 Republican  At Least a Bachelor's Degree <tibble [45 × 44]> Republican:At Lea…