Package 'tablecompare'

Show the contents of a data frame

Description

Show the contents of a data frame

Usage

contents(.data)

Arguments

.data

A data frame or data table

Value

A data.table with one row per column in .data and columns "column": The name of the column in .data, "class": the names of classes the column inherits from (as returned by class()), collapsed into a single string.

Examples

contents(ToothGrowth)

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Check for duplicate rows

Description

count_dupes() returns values of by variables for which the .data has multiple rows, along with the number of rows for each combination of values.

assert_unique() throws an error if there are multiple rows for any combination of by variable values

Usage

count_dupes(.data, by, setkey = FALSE)

assert_unique(.data, by, data_chr, by_chr)

Arguments

.data	A data frame or data table
by	tidy-select. Columns in .data
setkey	Logical. Should the output be keyed by by cols?
data_chr	optional. character. You can use this argument to manually specify the name of data shown in error messages. Useful when using these functions as checks inside other functions.
by_chr	optional. character. You can use this argument to manually specify the name of by shown in error messages. Useful when using these functions as checks inside other functions.

Value

count_dupes()

A data.table with the (filtered) by columns and an additional column "n_rows" which shows the number of rows in .data having the combination of by values shown in the output row.

assert_unique()

No return value. Called to throw an error depending on the input.

Examples

df <- read.table(text = "
x y z
1 6 1
2 6 2
3 7 3
3 7 4
4 3 5
4 3 6
", header = TRUE)

count_dupes(df, c(x, y))

## Not run: 
assert_unique(df, c(x, y))

## End(Not run)

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Check for existence of multiple values per group

Description

count_values() returns values of by variables for which the .data has multiple unique rows, along with the number of unique rows for each combination of values, only considering columns in col.

assert_single_value() throws an error if there are multiple unique rows for any combination of by variable values, only considering columns in col.

Usage

count_values(.data, col, by, setkey = FALSE)

assert_single_value(.data, col, by)

Arguments

.data	A data frame or data table
col	tidy-select. Columns in .data. When counting the number of unique rows, only the columns specified in col are considered.
by	tidy-select. Columns in .data.
setkey	Logical. Should the output be keyed by by cols?

Value

count_values()

A data.table with the (filtered) by columns and an additional column "n_vals" which shows the number of unique rows in .data having the combination of by values shown in the output row.

assert_single_value()

No return value. Called to throw an error depending on the input.

Examples

df <- read.table(text = "
x y z
a 1 3
a 1 3
a 2 4
a 2 4
a 2 2
b 1 1
b 1 2
", header = TRUE)

count_values(df, z, by = c(x, y))

## Not run: 
assert_single_value(df, z, by = c(x, y))

## End(Not run)

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Compare two data frames. Using a key-column common to both tables, see which rows are common and highlight differing values by column.

Description

Compare two data frames. Using a key-column common to both tables, see which rows are common and highlight differing values by column.

Usage

tblcompare(
  .data_a,
  .data_b,
  by,
  allow_bothNA = TRUE,
  ncol_by_out = 3,
  coerce = TRUE
)

value_diffs(comparison, col)

## S3 method for class 'tbcmp_compare'
value_diffs(comparison, col)

all_value_diffs(comparison)

## S3 method for class 'tbcmp_compare'
all_value_diffs(comparison)

Arguments

.data_a	A data frame or data table
.data_b	A data frame or data table
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_bothNA	Logical. If TRUE a missing value in both data frames is considered as equal
ncol_by_out	Number of by-columns to include in col_diffs and unmatched_rows output
coerce	Logical. If False only columns with the same class are compared.
comparison	An object of class "tbcmp_compare" (the output of a tablecompare::tablecompare() call)
col	tidy-select. A single column

Value

tblcompare()

A "tbcmp_compare"-class object, which is a list of data.table's having the following elements:

tables

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

by

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

summ

A data.table with one row per column common to .data_a and .data_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.table showing the rows in each input table where values are unequal, the values in each table, and one column for each of the first ncol_by_out by columns for the identified rows in the input tables.

unmatched_cols

A data.table 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.table which, for each row present in one input table but not the other, contains the columns "table": which table the row appears in, "i" the row number of the input row, and one column for each of the first ncol_by_out by columns for each row.

value_diffs()

A data.table with one row for each element of col found to be unequal between the input tables ( .data_a and .data_b from the original tblcompare() call) The output table has columns "i_a"/"i_b": the row number of the element in the input tables, "val_a"/"val_b": the value of col in the input tables, and one column for each of the first ncol_by_out by columns for the identified rows in the input tables.

all_value_diffs()

A data.table of the value_diffs() output for all columns having at least one value difference, combined row-wise into a single table. To facilitate this combination into a single table, the "val_a" and "val_b" columns are coerced to character.

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