pivot_longer.tbl_lazy {dbplyr}R Documentation

Pivot data from wide to long

Description

pivot_longer() "lengthens" data, increasing the number of rows and decreasing the number of columns. The inverse transformation is tidyr::pivot_wider().

Learn more in vignette("pivot", "tidyr").

While most functionality is identical there are some differences to pivot_longer() on local data frames:

Note that build_longer_spec() and pivot_longer_spec() do not work with remote tables.

Usage

## S3 method for class 'tbl_lazy'
pivot_longer(
  data,
  cols,
  ...,
  cols_vary,
  names_to = "name",
  names_prefix = NULL,
  names_sep = NULL,
  names_pattern = NULL,
  names_ptypes = NULL,
  names_transform = NULL,
  names_repair = "check_unique",
  values_to = "value",
  values_drop_na = FALSE,
  values_ptypes,
  values_transform = NULL
)

Arguments

data

A data frame to pivot.

cols

Columns to pivot into longer format.

...

Additional arguments passed on to methods.

cols_vary

Unsupported; included for compatibility with the generic.

names_to

A string specifying the name of the column to create from the data stored in the column names of data.

names_prefix

A regular expression used to remove matching text from the start of each variable name.

names_sep, names_pattern

If names_to contains multiple values, these arguments control how the column name is broken up.

names_ptypes

A list of column name-prototype pairs.

names_transform, values_transform

A list of column name-function pairs.

names_repair

What happens if the output has invalid column names?

values_to

A string specifying the name of the column to create from the data stored in cell values. If names_to is a character containing the special .value sentinel, this value will be ignored, and the name of the value column will be derived from part of the existing column names.

values_drop_na

If TRUE, will drop rows that contain only NAs in the value_to column.

values_ptypes

Not supported.

Details

The SQL translation basically works as follows:

  1. split the specification by its key columns i.e. by variables crammed into the column names.

  2. for each part in the split specification transmute() data into the following columns

  1. combine all the parts with union_all()

Examples


# See vignette("pivot") for examples and explanation

# Simplest case where column names are character data
memdb_frame(
  id = c("a", "b"),
  x = 1:2,
  y = 3:4
) %>%
  tidyr::pivot_longer(-id)


[Package dbplyr version 2.5.0 Index]