fill_gaps | R Documentation |
stable
fill_gaps(.data, ..., .full = FALSE, .start = NULL, .end = NULL)
.data |
A tsibble. |
... |
A set of name-value pairs. The values provided will only replace
missing values that were marked as "implicit", and will leave previously
existing
|
.full |
|
.start, .end |
Set custom starting/ending time that allows to expand the existing time spans. |
tidyr::fill, tidyr::replace_na for handling missing values NA
.
Other implicit gaps handling:
count_gaps()
,
has_gaps()
,
scan_gaps()
harvest <- tsibble( year = c(2010, 2011, 2013, 2011, 2012, 2014), fruit = rep(c("kiwi", "cherry"), each = 3), kilo = sample(1:10, size = 6), key = fruit, index = year ) # gaps as default `NA` fill_gaps(harvest, .full = TRUE) fill_gaps(harvest, .full = start()) fill_gaps(harvest, .full = end()) fill_gaps(harvest, .start = 2009, .end = 2016) full_harvest <- fill_gaps(harvest, .full = FALSE) full_harvest # replace gaps with a specific value harvest %>% fill_gaps(kilo = 0L) # replace gaps using a function by variable harvest %>% fill_gaps(kilo = sum(kilo)) # replace gaps using a function for each group harvest %>% group_by_key() %>% fill_gaps(kilo = sum(kilo)) # leaves existing `NA` untouched harvest[2, 3] <- NA harvest %>% group_by_key() %>% fill_gaps(kilo = sum(kilo, na.rm = TRUE)) # replace NA pedestrian %>% group_by_key() %>% fill_gaps(Count = as.integer(median(Count))) if (!requireNamespace("tidyr", quietly = TRUE)) { stop("Please install the 'tidyr' package to run these following examples.") } # use fill() to fill `NA` by previous/next entry pedestrian %>% group_by_key() %>% fill_gaps() %>% tidyr::fill(Count, .direction = "down")
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.