R: Pivot 'SpatVector' from wide to long

pivot_longer.SpatVector {tidyterra}

R Documentation

Pivot `SpatVector` from wide to long

Description

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

Learn more in tidyr::pivot_wider().

Usage

## S3 method for class 'SpatVector'
pivot_longer(
  data,
  cols,
  ...,
  cols_vary = "fastest",
  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 = NULL,
  values_transform = NULL
)

Arguments

`data`	A `SpatVector` to pivot.
`cols`	<`tidy-select`> Columns to pivot into longer format.
`...`	Additional arguments passed on to methods.
`cols_vary`	When pivoting `cols` into longer format, how should the output rows be arranged relative to their original row number? `"fastest"`, the default, keeps individual rows from `cols` close together in the output. This often produces intuitively ordered output when you have at least one key column from `data` that is not involved in the pivoting process. `"slowest"` keeps individual columns from `cols` close together in the output. This often produces intuitively ordered output when you utilize all of the columns from `data` in the pivoting process.
`names_to`	A character vector specifying the new column or columns to create from the information stored in the column names of `data` specified by `cols`. If length 0, or if `NULL` is supplied, no columns will be created. If length 1, a single column will be created which will contain the column names specified by `cols`. If length >1, multiple columns will be created. In this case, one of `names_sep` or `names_pattern` must be supplied to specify how the column names should be split. There are also two additional character values you can take advantage of: `NA` will discard the corresponding component of the column name. `".value"` indicates that the corresponding component of the column name defines the name of the output column containing the cell values, overriding `values_to` entirely.
`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_sep` takes the same specification as `separate()`, and can either be a numeric vector (specifying positions to break on), or a single string (specifying a regular expression to split on). `names_pattern` takes the same specification as `extract()`, a regular expression containing matching groups (`⁠()⁠`). If these arguments do not give you enough control, use `pivot_longer_spec()` to create a spec object and process manually as needed.
`names_ptypes`, `values_ptypes`	Optionally, a list of column name-prototype pairs. Alternatively, a single empty prototype can be supplied, which will be applied to all columns. A prototype (or ptype for short) is a zero-length vector (like `integer()` or `numeric()`) that defines the type, class, and attributes of a vector. Use these arguments if you want to confirm that the created columns are the types that you expect. Note that if you want to change (instead of confirm) the types of specific columns, you should use `names_transform` or `values_transform` instead.
`names_transform`, `values_transform`	Optionally, a list of column name-function pairs. Alternatively, a single function can be supplied, which will be applied to all columns. Use these arguments if you need to change the types of specific columns. For example, `names_transform = list(week = as.integer)` would convert a character variable called `week` to an integer. If not specified, the type of the columns generated from `names_to` will be character, and the type of the variables generated from `values_to` will be the common type of the input columns used to generate them.
`names_repair`	What happens if the output has invalid column names? The default, `"check_unique"` is to error if the columns are duplicated. Use `"minimal"` to allow duplicates in the output, or `"unique"` to de-duplicated by adding numeric suffixes. See `vctrs::vec_as_names()` for more options.
`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 `NA`s in the `value_to` column. This effectively converts explicit missing values to implicit missing values, and should generally be used only when missing values in `data` were created by its structure.

Value

A SpatVector object.

Methods

Implementation of the generic tidyr::pivot_longer() function.

`SpatVector`

The geometry column has a sticky behavior. This means that the result would have always the geometry of data.

Examples



library(dplyr)
library(tidyr)
library(ggplot2)
library(terra)

temp <- rast((system.file("extdata/cyl_temp.tif", package = "tidyterra")))
cyl <- vect(system.file("extdata/cyl.gpkg", package = "tidyterra")) %>%
  project(temp)

# Add average temp

temps <- terra::extract(temp, cyl, fun = "mean", na.rm = TRUE, xy = TRUE)
cyl_temp <- cbind(cyl, temps) %>%
  glimpse()

# And pivot long for plot
cyl_temp %>%
  pivot_longer(
    cols = tavg_04:tavg_06,
    names_to = "label",
    values_to = "temp"
  ) %>%
  ggplot() +
  geom_spatvector(aes(fill = temp)) +
  facet_wrap(~label, ncol = 1) +
  scale_fill_whitebox_c(palette = "muted")

[Package tidyterra version 0.6.1 Index]

Pivot SpatVector from wide to long