Package 'groupr'

Make a Single Column Grouping

Description

Takes a tibble and groups columns together into a single data column. All columns that are not row indices will be grouped, and the resulting column will be named data_name.

Usage

colgrp(x, data_name, index_name = "group")

Arguments

x	A tibble
data_name	A string, the name of the new column
index_name	A string, the name of the new column index

Value

A grouped tibble

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Group a Tibble With Inapplicable Groups

Description

Similar to dplyr::group_by(), this function groups a tibble while also marking certain groups as inapplicable.

Usage

group_by2(data, ...)

Arguments

data	A tibble to group
...	Arguments of the form var = c(val1, val2) or the name of a variable

Details

A grouped tibble has one or more grouping variables, where each unique combination of values identifies a group. This function allows some of the values to be marked inapplicable, such that the corresponding rows are not considered to be grouped on that variable at all.

Grouping variables, and inapplicable values, are passed as arguments in the form group_var = c(value1, value2, ...). Any included values will be marked inapplicable. If an argument has length 0 or is NULL, no values will be marked inapplicable.

Value

An igrouped tibble

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Set Column Grouping for a Structured Data Frame

Description

Takes a data frame where each non row index is a data frame column, and sets the corresponding column grouping.

Usage

infer_colgrps(x, index_name = "group", sep = "_")

Arguments

x	A tibble with data frame data columns
index_name	A name for the new column index
sep	A character used to join the data column and group names

Value

A grouped tibble

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Pivot with Inapplicable Groups

Description

Pivot a dataset by defining the way the current grouping will be transformed into a new one. A pivot to wider consumes a row grouping (created by group_by2) and produces a new set of columns. A pivot to longer consumes a column grouping and produces a new row grouping.

Usage

pivot_grps(x, rows = NULL, cols = NULL)

Arguments

x	A data frame
rows	A list of character vectors, defining the new row grouping
cols	A character vector, defining the new columns

Details

To pivot a column grouping to a row grouping, pass the specification of the new row grouping using the cols argument. The format is list(values_col = "oldcol_1", "oldcol_2", ...). This will take all the data from the old columns, combine them into a new column values_col, and automatically provide a grouping variable, which will be called name. The values of name will be the corresponding names of the old columns.

To pivot a row grouping to a column grouping, pass a grouped dataset (using group_by2) and specify which grouping variable should be consumed to produce a set of new columns.

Both arguments can be passed in one call, in which case rows will be handled first, followed by cols.

See the introduction vignette for more details and examples.

Value

A pivoted data frame with the new grouping

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Separate Columns By a Character

Description

Creates a column index by interpreting each column name as a data column name and a group name separated by sep. Only columns that are not row indices are used. sep must occur exactly once in each column name.

Usage

sep_colgrp(x, sep, index_name = "group")

Arguments

x	A tibble
sep	A character delimiting the two parts of the name
index_name	A name for the new column index

Value

A grouped tibble

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Ungroup a Tibble With Inapplicable Groups

Description

Ungroup method for tibbles that have inapplicable groups.

Usage

## S3 method for class 'igrouped_df'
ungroup(x, ...)

Arguments

x	An igrouped tibble (as created by group_by2)
...	Ignored. All variables are removed from the grouping.

Value

A tibble with no groups. The "groups" attribute will be set to contain one column, .rows, with a single value that lists all rows.

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