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A toolset for interactively exploring the differences between two data frames.
install.packages("versus")
# Or install the development version from GitHub with
# pak::pak("eutwt/versus")The two data frames below are used as an example to demonstrate functionality
library(versus)
example_df_a
#> # A tibble: 9 × 9
#> car mpg cyl disp hp drat wt vs am
#> <chr> <dbl> <int> <dbl> <int> <dbl> <dbl> <int> <int>
#> 1 Duster 360 14.3 8 360 245 3.21 3.57 0 0
#> 2 Mazda RX4 Wag 21 6 160 110 3.9 2.88 0 1
#> 3 Merc 230 22.8 4 141. 95 3.92 3.15 1 0
#> 4 Datsun 710 22.8 NA 109 93 3.85 2.32 1 1
#> 5 Merc 240D 24.4 4 147. 62 3.69 3.19 1 0
#> 6 Hornet 4 Drive 21.4 6 259 110 3.08 3.22 1 0
#> 7 Mazda RX4 21 6 160 110 3.9 2.62 0 1
#> 8 Valiant 18.1 6 225 105 2.76 3.46 1 0
#> 9 Merc 280 19.2 6 168. 123 3.92 3.44 1 0
example_df_b
#> # A tibble: 10 × 9
#> car wt mpg hp cyl disp carb drat vs
#> <chr> <dbl> <dbl> <int> <int> <dbl> <int> <dbl> <int>
#> 1 Merc 240D 3.19 26.4 62 4 147. 2 3.69 1
#> 2 Valiant 3.46 18.1 105 6 225 1 2.76 1
#> 3 Duster 360 3.57 16.3 245 8 360 4 3.21 0
#> 4 Datsun 710 2.32 22.8 93 NA 108 1 3.85 1
#> 5 Merc 280C 3.44 17.8 123 6 168. 4 3.92 1
#> 6 Merc 280 3.44 19.2 123 6 168. 4 3.92 1
#> 7 Hornet 4 Drive 3.22 21.4 110 6 258 1 3.08 1
#> 8 Merc 450SE 4.07 16.4 180 8 276. 3 3.07 0
#> 9 Merc 230 3.15 22.8 95 4 141. 2 3.92 1
#> 10 Mazda RX4 Wag 2.88 21 110 6 160 4 3.9 0Use compare() to create a comparison of two tables.
A comparison contains:
compare()$intersection: columns in both tables and rows with differing valuescompare()$unmatched_cols: columns in only one tablecompare()$unmatched_rows: rows in only one tablecomparison <- compare(example_df_a, example_df_b, by = car)
comparison
#> $tables
#> # A tibble: 2 × 4
#> table expr nrow ncol
#> <chr> <chr> <int> <int>
#> 1 table_a example_df_a 9 9
#> 2 table_b example_df_b 10 9
#>
#> $by
#> # A tibble: 1 × 3
#> column class_a class_b
#> <chr> <chr> <chr>
#> 1 car character character
#>
#> $intersection
#> # A tibble: 7 × 5
#> column n_diffs class_a class_b diff_rows
#> <chr> <int> <chr> <chr> <list>
#> 1 mpg 2 numeric numeric <tibble [2 × 2]>
#> 2 cyl 0 integer integer <tibble [0 × 2]>
#> 3 disp 2 numeric numeric <tibble [2 × 2]>
#> 4 hp 0 integer integer <tibble [0 × 2]>
#> 5 drat 0 numeric numeric <tibble [0 × 2]>
#> 6 wt 0 numeric numeric <tibble [0 × 2]>
#> 7 vs 0 integer integer <tibble [0 × 2]>
#>
#> $unmatched_cols
#> # A tibble: 2 × 2
#> table column
#> <chr> <chr>
#> 1 a am
#> 2 b carb
#>
#> $unmatched_rows
#> # A tibble: 3 × 3
#> table car row
#> <chr> <chr> <int>
#> 1 a Mazda RX4 7
#> 2 b Merc 280C 5
#> 3 b Merc 450SE 8Use value_diffs() to see the values that are different.
comparison |>
value_diffs(disp)
#> # A tibble: 2 × 3
#> disp_a disp_b car
#> <dbl> <dbl> <chr>
#> 1 109 108 Datsun 710
#> 2 259 258 Hornet 4 Drive
comparison |>
value_diffs_stacked(c(mpg, disp))
#> # A tibble: 4 × 4
#> column val_a val_b car
#> <chr> <dbl> <dbl> <chr>
#> 1 mpg 14.3 16.3 Duster 360
#> 2 mpg 24.4 26.4 Merc 240D
#> 3 disp 109 108 Datsun 710
#> 4 disp 259 258 Hornet 4 DriveUse weave_diffs_*() to see the differing values in context.
comparison |>
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
comparison |>
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
comparison |>
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 1Use slice_diffs() to get the rows with differing values from one table.
comparison |>
slice_diffs("a", mpg)
#> # A tibble: 2 × 9
#> car mpg cyl disp hp drat wt vs am
#> <chr> <dbl> <int> <dbl> <int> <dbl> <dbl> <int> <int>
#> 1 Duster 360 14.3 8 360 245 3.21 3.57 0 0
#> 2 Merc 240D 24.4 4 147. 62 3.69 3.19 1 0Use slice_unmatched() to get the rows unmatched rows from one or both tables.
comparison |>
slice_unmatched("a")
#> # A tibble: 1 × 9
#> car mpg cyl disp hp drat wt vs am
#> <chr> <dbl> <int> <dbl> <int> <dbl> <dbl> <int> <int>
#> 1 Mazda RX4 21 6 160 110 3.9 2.62 0 1
comparison |>
slice_unmatched_both()
#> # A tibble: 3 × 9
#> table car mpg cyl disp hp drat wt vs
#> <chr> <chr> <dbl> <int> <dbl> <int> <dbl> <dbl> <int>
#> 1 a Mazda RX4 21 6 160 110 3.9 2.62 0
#> 2 b Merc 280C 17.8 6 168. 123 3.92 3.44 1
#> 3 b Merc 450SE 16.4 8 276. 180 3.07 4.07 0Use summary() to see what kind of differences were found
summary(comparison)
#> # A tibble: 4 × 2
#> difference found
#> <chr> <lgl>
#> 1 value_diffs TRUE
#> 2 unmatched_cols TRUE
#> 3 unmatched_rows TRUE
#> 4 class_diffs FALSEThese binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.