Replace NA by Aggregation
Generic function for replacing each
NA with aggregated
values. This allows imputing by the overall mean, by monthly means,
na.aggregate(object, ...) ## S3 method for class 'default': na.aggregate(object, by = 1, \dots, FUN = mean, na.rm = FALSE, maxgap = Inf)
- an object.
- a grouping variable corresponding to
object, or a function to be applied to
time(object)to generate the groups.
- further arguments passed to
byis a function.
- function to apply to the non-missing values in each group
- logical. Should any remaining
NAs be removed?
- maximum number of consecutive
NAs to fill. Any longer gaps will be left unchanged.
- An object in which each
NAin the input object is replaced by the mean (or other function) of its group, defined by
by. This is done for each series in a multi-column object. Common choices for the aggregation group are a year, a month, all calendar months, etc. If a group has no non-missing values, the default aggregation function
na.rm = TRUEto omit such remaining missing values.
z <- zoo(c(1, NA, 3:9), c(as.Date("2010-01-01") + 0:2, as.Date("2010-02-01") + 0:2, as.Date("2011-01-01") + 0:2)) ## overall mean na.aggregate(z) ## group by months na.aggregate(z, as.yearmon) ## group by calendar months na.aggregate(z, months) ## group by years na.aggregate(z, format, "%Y")
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