R: Tidyverse methods for tsibble

tsibble-tidyverse {tsibble} | R Documentation

## Tidyverse methods for tsibble

### Description

- `arrange()`: if not arranging key and index in past-to-future order, a warning is likely to be issued.

- `slice()`: if row numbers are not in ascending order, a warning is likely to be issued.

- `select()`: keeps the variables you mention as well as the index.

- `transmute()`: keeps the variable you operate on, as well as the index and key.

- `summarise()` reduces a sequence of values over time instead of a single summary, as well as dropping empty keys/groups.

### Usage

    ## S3 method for class 'tbl_ts'
    arrange(.data, ...)

    ## S3 method for class 'tbl_ts'
    filter(.data, ..., .preserve = FALSE)

    ## S3 method for class 'tbl_ts'
    slice(.data, ..., .preserve = FALSE)

    ## S3 method for class 'tbl_ts'
    select(.data, ...)

    ## S3 method for class 'tbl_ts'
    rename(.data, ...)

    ## S3 method for class 'tbl_ts'
    mutate(.data, ...)

    ## S3 method for class 'tbl_ts'
    transmute(.data, ...)

    ## S3 method for class 'tbl_ts'
    summarise(.data, ...)

    ## S3 method for class 'tbl_ts'
    gather(data, key = "key", value = "value", ...,
      na.rm = FALSE, convert = FALSE, factor_key = FALSE)

    ## S3 method for class 'tbl_ts'
    spread(data, key, value, ...)

    ## S3 method for class 'tbl_ts'
    nest(.data, ...)

### Arguments

`.data` | A `tbl_ts`.
`...` | Same arguments accepted as its tidyverse generic.
`.preserve` | when `FALSE` (the default), the grouping structure is recalculated based on the resulting data, otherwise it is kept as is.
`data` | A data frame.
`key` | Names of new key and value columns, as strings or symbols. This argument is passed by expression and supports quasiquotation (you can unquote strings and symbols). The name is captured from the expression with `rlang::ensym()` (note that this kind of interface where symbols do not represent actual objects is now discouraged in the tidyverse; we support it here for backward compatibility).
`value` | Names of new key and value columns, as strings or symbols. This argument is passed by expression and supports quasiquotation (you can unquote strings and symbols). The name is captured from the expression with `rlang::ensym()` (note that this kind of interface where symbols do not represent actual objects is now discouraged in the tidyverse; we support it here for backward compatibility).
`na.rm` | If `TRUE`, will remove rows from output where the value column is `NA`.
`convert` | If `TRUE` will automatically run `type.convert()` on the key column. This is useful if the column types are actually numeric, integer, or logical.
`factor_key` | If `FALSE`, the default, the key values will be stored as a character vector. If `TRUE`, will be stored as a factor, which preserves the original ordering of the columns.

### Details

Column-wise verbs, including `select()`, `transmute()`, `summarise()`, `mutate()` & `transmute()`, keep the time context hanging around. That is, the index variable cannot be dropped for a tsibble. If any key variable is changed, it will validate whether it's a tsibble internally. Use `as_tibble()` to leave off the time context.

### Examples

    library(dplyr, warn.conflicts = FALSE)
    # Sum over sensors
    pedestrian %>%
      index_by() %>%
      summarise(Total = sum(Count))
    # shortcut
    pedestrian %>%
      summarise(Total = sum(Count))
    # Back to tibble
    pedestrian %>%
      as_tibble() %>%
      summarise(Total = sum(Count))
    library(tidyr)
    # example from tidyr
    stocks <- tsibble(
      time = as.Date('2009-01-01') + 0:9,
      X = rnorm(10, 0, 1),
      Y = rnorm(10, 0, 2),
      Z = rnorm(10, 0, 4)
    )
    (stocksm <- stocks %>% gather(stock, price, -time))
    stocksm %>% spread(stock, price)
    nested_stock <- stocksm %>%
      nest(-stock)
    stocksm %>%
      group_by(stock) %>%
      nest()

[Package tsibble version 0.8.2 Index]