Get differences in context

Usage

weave_diffs_long(comparison, column = everything())

weave_diffs_wide(comparison, column = everything(), suffix = NULL)

Arguments

comparison: The output of compare()
column: <tidy-select>. A row will be in the output if the comparison shows differing values for any columns matching this argument
suffix: A character vector of length 2 providing suffixes appended to the renamed columns in weave_diffs_wide(). Set to NULL (the default) to use paste0("_", table_id). The first suffix is applied to values from table_a, the second to values from table_b.

Value

weave_diffs_wide(): The input table_a filtered to rows where differing values exist for one of the columns selected by column. The selected columns with differences will be in the result twice, one for each input table.
weave_diffs_long(): Input tables are filtered to rows where differing values exist for one of the columns selected by column. These two sets of rows (one for each input table) are interleaved row-wise.

Examples

comp <- compare(example_df_a, example_df_b, by = car)
comp |> weave_diffs_wide(disp)
#> # A tibble: 2 × 9
#>   car              mpg   cyl disp_a disp_b    hp  drat    wt    vs
#>   <chr>          <dbl> <int>  <dbl>  <dbl> <int> <dbl> <dbl> <int>
#> 1 Datsun 710      22.8    NA    109    108    93  3.85  2.32     1
#> 2 Hornet 4 Drive  21.4     6    259    258   110  3.08  3.22     1
comp |> weave_diffs_wide(c(mpg, disp))
#> # A tibble: 4 × 10
#>   car            mpg_a mpg_b   cyl disp_a disp_b    hp  drat    wt    vs
#>   <chr>          <dbl> <dbl> <int>  <dbl>  <dbl> <int> <dbl> <dbl> <int>
#> 1 Duster 360      14.3  16.3     8   360    360    245  3.21  3.57     0
#> 2 Merc 240D       24.4  26.4     4   147.   147.    62  3.69  3.19     1
#> 3 Datsun 710      22.8  22.8    NA   109    108     93  3.85  2.32     1
#> 4 Hornet 4 Drive  21.4  21.4     6   259    258    110  3.08  3.22     1
comp |> weave_diffs_wide(c(mpg, disp), suffix = c("", "_new"))
#> # A tibble: 4 × 10
#>   car              mpg mpg_new   cyl  disp disp_new    hp  drat    wt    vs
#>   <chr>          <dbl>   <dbl> <int> <dbl>    <dbl> <int> <dbl> <dbl> <int>
#> 1 Duster 360      14.3    16.3     8  360      360    245  3.21  3.57     0
#> 2 Merc 240D       24.4    26.4     4  147.     147.    62  3.69  3.19     1
#> 3 Datsun 710      22.8    22.8    NA  109      108     93  3.85  2.32     1
#> 4 Hornet 4 Drive  21.4    21.4     6  259      258    110  3.08  3.22     1
comp |> weave_diffs_long(disp)
#> # A tibble: 4 × 9
#>   table car              mpg   cyl  disp    hp  drat    wt    vs
#>   <chr> <chr>          <dbl> <int> <dbl> <int> <dbl> <dbl> <int>
#> 1 a     Datsun 710      22.8    NA   109    93  3.85  2.32     1
#> 2 b     Datsun 710      22.8    NA   108    93  3.85  2.32     1
#> 3 a     Hornet 4 Drive  21.4     6   259   110  3.08  3.22     1
#> 4 b     Hornet 4 Drive  21.4     6   258   110  3.08  3.22     1
comp |> weave_diffs_long(c(mpg, disp))
#> # A tibble: 8 × 9
#>   table car              mpg   cyl  disp    hp  drat    wt    vs
#>   <chr> <chr>          <dbl> <int> <dbl> <int> <dbl> <dbl> <int>
#> 1 a     Duster 360      14.3     8  360    245  3.21  3.57     0
#> 2 b     Duster 360      16.3     8  360    245  3.21  3.57     0
#> 3 a     Merc 240D       24.4     4  147.    62  3.69  3.19     1
#> 4 b     Merc 240D       26.4     4  147.    62  3.69  3.19     1
#> 5 a     Datsun 710      22.8    NA  109     93  3.85  2.32     1
#> 6 b     Datsun 710      22.8    NA  108     93  3.85  2.32     1
#> 7 a     Hornet 4 Drive  21.4     6  259    110  3.08  3.22     1
#> 8 b     Hornet 4 Drive  21.4     6  258    110  3.08  3.22     1