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Create "long" skim output

Source: R/reshape.R
to_long.Rd

Skim results returned as a tidy long data frame with four columns: variable, type, stat and formatted.

Usage

to_long(.data, ..., skim_fun = skim)

# Default S3 method
to_long(.data, ..., skim_fun = skim)

# S3 method for class 'skim_df'
to_long(.data, ..., skim_fun = skim)

Arguments

.data

A data frame or an object that can be coerced into a data frame.

...

Columns to select for skimming. When none are provided, the default is to skim all columns.

skim_fun

The skim function used.

Value

A tibble

Methods (by class)

  • to_long(default): Skim a data frame and convert the results to a long data frame.

  • to_long(skim_df): Transform a skim_df to a long data frame.

Examples

to_long(iris)
#> # A tibble: 45 × 4
#>    skim_type skim_variable stat              formatted                
#>    <chr>     <chr>         <chr>             <chr>                    
#>  1 factor    Species       n_missing         0                        
#>  2 factor    Species       complete_rate     1                        
#>  3 factor    Species       factor.ordered    FALSE                    
#>  4 factor    Species       factor.n_unique   3                        
#>  5 factor    Species       factor.top_counts set: 50, ver: 50, vir: 50
#>  6 numeric   Sepal.Length  n_missing         0                        
#>  7 numeric   Sepal.Length  complete_rate     1                        
#>  8 numeric   Sepal.Length  numeric.mean      5.84333333333333         
#>  9 numeric   Sepal.Length  numeric.sd        0.828066127977863        
#> 10 numeric   Sepal.Length  numeric.p0        4.3                      
#> # ℹ 35 more rows
to_long(skim(iris))
#> # A tibble: 45 × 4
#>    skim_type skim_variable stat              formatted                
#>    <chr>     <chr>         <chr>             <chr>                    
#>  1 factor    Species       n_missing         0                        
#>  2 factor    Species       complete_rate     1                        
#>  3 factor    Species       factor.ordered    FALSE                    
#>  4 factor    Species       factor.n_unique   3                        
#>  5 factor    Species       factor.top_counts set: 50, ver: 50, vir: 50
#>  6 numeric   Sepal.Length  n_missing         0                        
#>  7 numeric   Sepal.Length  complete_rate     1                        
#>  8 numeric   Sepal.Length  numeric.mean      5.84333333333333         
#>  9 numeric   Sepal.Length  numeric.sd        0.828066127977863        
#> 10 numeric   Sepal.Length  numeric.p0        4.3                      
#> # ℹ 35 more rows