tsibble-tidyverse | R Documentation |
Current dplyr verbs that tsibble has support for:
dplyr::filter()
, dplyr::slice()
, dplyr::arrange()
dplyr::select()
, dplyr::transmute()
, dplyr::mutate()
, dplyr::relocate()
,
dplyr::summarise()
, dplyr::group_by()
dplyr::left_join()
, dplyr::right_join()
, dplyr::full_join()
,
dplyr::inner_join()
, dplyr::semi_join()
, dplyr::anti_join()
,
dplyr::nest_join()
dplyr::bind_rows()
, dplyr::bind_cols()
Current tidyr verbs that tsibble has support for:
tidyr::pivot_longer()
, tidyr::pivot_wider()
,
tidyr::gather()
, tidyr::spread()
tidyr::nest()
, tidyr::fill()
, tidyr::drop_na()
The index variable cannot be dropped for a tsibble object.
When any key variable is modified, a check on the validity of the resulting tsibble will be performed internally.
Use as_tibble()
to convert tsibble to a general data frame.
A warning is likely to be issued, if observations are not arranged in past-to-future order.
Joining with other data sources triggers the check on the validity of the resulting tsibble.
library(dplyr, warn.conflicts = FALSE) # `summarise()` a tsibble always aggregates over time # 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) 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 %>% pivot_longer(-time, names_to = "stock", values_to = "price")) stocksm %>% pivot_wider(names_from = stock, values_from = price)
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