na.locf {zoo} | R Documentation |
Generic function for replacing each NA
with the most recent
non-NA
prior to it.
na.locf(object, na.rm = TRUE, ...) ## Default S3 method: na.locf(object, na.rm = TRUE, fromLast, rev, maxgap = Inf, ...)
object |
an object. |
na.rm |
logical. Should leading NA s be removed? |
fromLast |
logical. Causes observations to be carried backward rather
than forward. Default is FALSE .
This corresponds to NOCB (next observation carried backward). |
rev |
Use fromLast instead. This argument will
be eliminated in the future in favor of fromLast . |
maxgap |
maximum number of consecutive NA s to
fill. Any longer gaps will be left unchanged. |
... |
further arguments passed to methods. |
An object in which each NA
in the input object is replaced
by the most recent non-NA
prior to it. If there are no earlier non-NA
s then
the NA
is omitted (if na.rm = TRUE
) or it is not replaced (if na.rm = FALSE
).
Note that if a multi-column zoo object has a column entirely composed of
NA
then with na.rm = TRUE
, the default,
the above implies that the resulting object will have
zero rows. Use na.rm = FALSE
to preserve the NA
values instead.
az <- zoo(1:6) bz <- zoo(c(2,NA,1,4,5,2)) na.locf(bz) na.locf(bz, fromLast = TRUE) cz <- zoo(c(NA,9,3,2,3,2)) na.locf(cz) # generate and fill in missing dates # by merging with a zero width series having those dates # and then applying na.locf z <- zoo(c(0.007306621, 0.007659046, 0.007681013, 0.007817548, 0.007847579, 0.007867313), as.Date(c("1993-01-01", "1993-01-09", "1993-01-16", "1993-01-23", "1993-01-30", "1993-02-06"))) dd <- seq(start(z), end(z), "day") na.locf(merge(z, zoo(, dd))) ## get 5th of every month or most recent date prior to 5th if 5th missing. ## Result has index of the date actually used. z <- zoo(c(1311.56, 1309.04, 1295.5, 1296.6, 1286.57, 1288.12, 1289.12, 1289.12, 1285.33, 1307.65, 1309.93, 1311.46, 1311.28, 1308.11, 1301.74, 1305.41, 1309.72, 1310.61, 1305.19, 1313.21, 1307.85, 1312.25, 1325.76), as.Date(c(13242, 13244, 13245, 13248, 13249, 13250, 13251, 13252, 13255, 13256, 13257, 13258, 13259, 13262, 13263, 13264, 13265, 13266, 13269, 13270, 13271, 13272, 13274))) # z.na is same as z but with missing days added (with NAs) # It is formed by merging z with a zero with series having all the dates. rng <- range(time(z)) z.na <- merge(z, zoo(, seq(rng[1], rng[2], by = "day"))) # use na.locf to bring values forward picking off 5th of month na.locf(z.na)[as.POSIXlt(time(z.na))$mday == 5] ## this is the same as last one except instead of always using the ## 5th of month in the result we show the date actually used # idx has NAs wherever z.na does but has 1, 2, 3, ... instead of # z.na's data values (so idx can be used for indexing) idx <- na.locf(seq_along(z.na) + (0 * z.na)) # pick off those elements of z.na that correspond to 5th z.na[idx[as.POSIXlt(time(z.na))$mday == 5]] ## only fill single-day gaps merge(z.na, filled1 = na.locf(z.na, maxgap = 1))