Drop rows containing missing values in a column of nested data frames

nest_drop_na() is used to drop rows from each data frame in a column of nested data frames.

Usage

nest_drop_na(.data, .nest_data, ...)

Arguments

.data

A data frame, data frame extension (e.g., a tibble), or a lazy data frame (e.g., from dbplyr or dtplyr).

.nest_data

A list-column containing data frames

...

Columns within .nest_data to inspect for missing values. If empty, all columns within each dataframe in .nest_data are used.

Value

An object of the same type as .data. Each object in the column .nest_data

will have rows dropped according to the presence of NAs.

Details

nest_drop_na() is a wrapper for tidyr::drop_na() and maintains the functionality of drop_na() within each nested data frame. For more information on drop_na() please refer to the documentation in 'tidyr'.

See also

Other tidyr verbs: nest_extract(), nest_fill(), nest_replace_na(), nest_separate(), nest_unite()

Examples

gm <- gapminder::gapminder 

# randomly insert NAs into the dataframe & nest
set.seed(123) 
gm <- 
  gm %>% 
  dplyr::mutate(pop = dplyr::if_else(runif(nrow(gm)) >= 0.9, 
                                     NA_integer_, 
                                     pop))
  
gm_nest <- gm %>% tidyr::nest(country_data = -continent)

# drop rows where an NA exists in column `pop`
gm_nest %>% 
  nest_drop_na(country_data, pop)
#> # A tibble: 5 × 2
#>   continent country_data      
#>   <fct>     <list>            
#> 1 Asia      <tibble [364 × 5]>
#> 2 Europe    <tibble [326 × 5]>
#> 3 Africa    <tibble [572 × 5]>
#> 4 Americas  <tibble [273 × 5]>
#> 5 Oceania   <tibble [23 × 5]>