aggregate_index(.data, .window, ..., .offset = "end", .bin_size = NULL)
Temporal aggregations to include. The default (NULL) will automatically identify appropriate temporal aggregations. This can be specified in several ways (see details).
data-masking> Name-value pairs of
summary functions. The name will be the name of the variable in the result.
The value can be:
A vector of length 1, e.g.
A data frame, to add multiple columns from a single expression.
Returning values with size 0 or >1 was
deprecated as of 1.1.0. Please use
reframe() for this instead.
Offset the temporal aggregation windows to align with the start or end of the data. If FALSE, no offset will be applied (giving common breakpoints for temporal bins.)
Temporary. Define the number of observations in each temporal bucket
This feature is very experimental. It currently allows for temporal aggregation of daily data as a proof of concept.
.window can be specified in several ways:
A character string, containing one of "day", "week", "month", "quarter" or "year". This can optionally be preceded by a (positive or negative) integer and a space, or followed by "s".
A number, taken to be in days.
library(tsibble) pedestrian %>% # Currently only supports daily data index_by(Date) %>% dplyr::summarise(Count = sum(Count)) %>% # Compute weekly aggregates fabletools:::aggregate_index("1 week", Count = sum(Count)) #> # A tsibble: 104 x 2 [7D] #> Date Count #> <date> <int> #> 1 2015-01-03 182896 #> 2 2015-01-10 231513 #> 3 2015-01-17 348879 #> 4 2015-01-24 313666 #> 5 2015-01-31 238603 #> 6 2015-02-07 219104 #> 7 2015-02-14 377340 #> 8 2015-02-21 530409 #> 9 2015-02-28 444666 #> 10 2015-03-07 614122 #> # ℹ 94 more rows