Package 'versus'

Compare two data frames

Description

compare() creates a representation of the differences between two tables, along with a shallow copy of the tables. This output is used as the comparison argument when exploring the differences further with other versus functions e.g. ⁠slice_*()⁠ and ⁠weave_*()⁠.

Usage

compare(table_a, table_b, by, allow_both_NA = TRUE, coerce = TRUE)

Arguments

table_a	A data frame
table_b	A data frame
by	<tidy-select>. Selection of columns to use when matching rows between .data_a and .data_b. Both data frames must be unique on by.
allow_both_NA	Logical. If TRUE a missing value in both data frames is considered as equal
coerce	Logical. If FALSE and columns from the input tables have differing classes, the function throws an error.

Value

compare()

A list of data frames having the following elements:

tables

A data frame with one row per input table showing the number of rows and columns in each.

by

A data frame with one row per by column showing the class of the column in each of the input tables.

intersection

A data frame with one row per column common to table_a and table_b and columns "n_diffs" showing the number of values which are different between the two tables, "class_a"/"class_b" the class of the column in each table, and "value_diffs" a (nested) data frame showing the the row indices with differing values

unmatched_cols

A data frame with one row per column which is in one input table but not the other and columns "table": which table the column appears in, "column": the name of the column, and "class": the class of the column.

unmatched_rows

A data frame which, for each row present in one input table but not the other, contains the column "table" showing which table the row appears in and the by columns for that row.

data.table inputs

If the input is a data.table, you may want compare() to make a deep copy instead of a shallow copy so that future changes to the table don't affect the comparison. To achieve this, you can set options(versus.copy_data_table = TRUE).

Examples

compare(example_df_a, example_df_b, by = car)

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Modified version of datasets::mtcars - version a

Description

A version of mtcars with some values altered and some rows/columns removed. Not for informational purposes, used only to demonstrate the comparison of two slightly different data frames. Since some values were altered at random, the values do not necessarily reflect the true original values. The variables are as follows:

Usage

example_df_a

Format

A data frame with 9 rows and 9 variables:

car

The rowname in the corresponding datasets::mtcars row

mpg

Miles/(US) gallon

cyl

Number of cylinders

disp

Displacement (cu.in.)

hp

Gross horsepower

drat

Rear axle ratio

wt

Weight (1000 lbs)

vs

Engine (0 = V-shaped, 1 = straight)

am

Transmission (0 = automatic, 1 = manual)

Source

Sourced from the CRAN datasets package, with modified values. Originally from Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411.

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Modified version of datasets::mtcars - version b

Description

A version of mtcars with some values altered and some rows/columns removed. Not for informational purposes, used only to demonstrate the comparison of two slightly different data frames. Since some values were altered at random, the values do not necessarily reflect the true original values. The variables are as follows:

Usage

example_df_b

Format

A data frame with 9 rows and 9 variables:

car

The rowname in the corresponding datasets::mtcars row

wt

Weight (1000 lbs)

mpg

Miles/(US) gallon

hp

Gross horsepower

cyl

Number of cylinders

disp

Displacement (cu.in.)

carb

Number of carburetors

drat

Rear axle ratio

vs

Engine (0 = V-shaped, 1 = straight)

Source

Sourced from the CRAN datasets package, with modified values. Originally from Henderson and Velleman (1981), Building multiple regression models interactively. Biometrics, 37, 391–411.

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Get rows with differing values

Description

Get rows with differing values

Usage

slice_diffs(comparison, table, column = everything())

Arguments

comparison	The output of compare()
table	One of "a" or "b" indicating which of the tables used to create comparison should be sliced
column	<tidy-select>. A row will be in the output if the comparison shows differing values for any columns matching this argument

Value

The input table is filtered to the rows for which comparison shows differing values for one of the columns selected by column

Examples

comp <- compare(example_df_a, example_df_b, by = car)
comp |> slice_diffs("a", mpg)
comp |> slice_diffs("b", mpg)
comp |> slice_diffs("a", c(mpg, disp))

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Get rows in only one table

Description

Get rows in only one table

Usage

slice_unmatched(comparison, table)

slice_unmatched_both(comparison)

Arguments

comparison	The output of compare()
table	One of "a" or "b" indicating which of the tables used to create comparison should be sliced

Value

slice_unmatched()	The table identified by table is filtered to the rows comparison shows as not appearing in the other table
slice_unmatched_both()	The output of slice_unmatched() for both input tables row-stacked with a column table indicating which table the row is from. The output contains only columns present in both tables.

Examples

comp <- compare(example_df_a, example_df_b, by = car)
comp |> slice_unmatched("a")
comp |> slice_unmatched("b")

# slice_unmatched(comp, "a") output is the same as
example_df_a |> dplyr::anti_join(example_df_b, by = comp$by$column)

comp |> slice_unmatched_both()

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Get the differing values from a comparison

Description

Get the differing values from a comparison

Usage

value_diffs(comparison, column)

value_diffs_stacked(comparison, column = everything())

Arguments

comparison	The output of compare()
column	<tidy-select>. The output will show the differing values for the provided columns.

Value

value_diffs()	A data frame with one row for each element of col found to be unequal between the input tables ( table_a and table_b from the original compare() output) The output table has the column specified by column from each of the input tables, plus the by columns.
value_diffs_stacked(), value_diffs_all()	A data frame containing the value_diffs() outputs for the specified columns combined row-wise using dplyr::bind_rows(). If dplyr::bind_rows() is not possible due to incompatible types, values are converted to character first. value_diffs_all() is the same as value_diffs_stacked() with column = everything()

Examples

comp <- compare(example_df_a, example_df_b, by = car)
value_diffs(comp, disp)
value_diffs_stacked(comp, c(disp, mpg))

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Get differences in context

Description

Get differences in context

Usage

weave_diffs_long(comparison, column = everything())

weave_diffs_wide(comparison, column = everything())

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

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)
comp |> weave_diffs_wide(c(mpg, disp))
comp |> weave_diffs_long(disp)
comp |> weave_diffs_long(c(mpg, disp))

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