R: Table Transformer: obtain a summary table for string columns

tt_string_info {pointblank}

R Documentation

Table Transformer: obtain a summary table for string columns

Description

With any table object, you can produce a summary table that is scoped to string-based columns. The output summary table will have a leading column called ".param." with labels for each of the three rows, each corresponding to the following pieces of information pertaining to string length:

Mean String Length ("length_mean")
Minimum String Length ("length_min")
Maximum String Length ("length_max")

Only string data from the input table will generate columns in the output table. Column names from the input will be used in the output, preserving order as well.

Usage

tt_string_info(tbl)

Arguments

tbl

A data table

⁠obj:<tbl_*>⁠ // required

A table object to be used as input for the transformation. This can be a data frame, a tibble, a tbl_dbi object, or a tbl_spark object.

Value

A tibble object.

Examples

Get string information for the string-based columns in the game_revenue dataset that is included in the pointblank package.

tt_string_info(tbl = game_revenue)
#> # A tibble: 3 x 7
#>   .param.     player_id session_id item_type item_name acquisition country
#>   <chr>           <dbl>      <dbl>     <dbl>     <dbl>       <dbl>   <dbl>
#> 1 length_mean        15         24      2.22      7.35        7.97    8.53
#> 2 length_min         15         24      2         5           5       5   
#> 3 length_max         15         24      3        11          14      14

Ensure that player_id and session_id values always have the same fixed numbers of characters (15 and 24, respectively) throughout the table.

tt_string_info(tbl = game_revenue) %>%
  col_vals_equal(
    columns = player_id,
    value = 15
  ) %>%
  col_vals_equal(
    columns = session_id,
    value = 24
  )
#> # A tibble: 3 x 7
#>   .param.     player_id session_id item_type item_name acquisition country
#>   <chr>           <dbl>      <dbl>     <dbl>     <dbl>       <dbl>   <dbl>
#> 1 length_mean        15         24      2.22      7.35        7.97    8.53
#> 2 length_min         15         24      2         5           5       5   
#> 3 length_max         15         24      3        11          14      14

We see data, and not an error, so both validations were successful!

Let's use a tt_string_info()-transformed table with the test_col_vals_lte() to check that the maximum string length in column f of the small_table dataset is no greater than 4.

tt_string_info(tbl = small_table) %>%
  test_col_vals_lte(
    columns = f,
    value = 4
  )
#> [1] TRUE

Function ID

12-2