Description Usage Arguments Value See Also Examples
Generic function for replacing each NA
with the most recent
non-NA
prior to it.
1 2 3 4 5 6 7 8 9 |
object |
an object. |
na_rm |
logical. Should leading |
... |
further arguments passed to methods. |
fromLast |
logical. Causes observations to be carried backward rather
than forward. Default is |
rev |
Use |
maxgap |
Runs of more than |
rule |
See |
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
).
The arguments x
and xout
can be used in which case they have
the same meaning as in approx
.
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.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | 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
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")))
g <- seq(start(z), end(z), "day")
na_locf(z, xout = g)
# similar but use a 2 second grid
z <- zoo(1:9, as.POSIXct(c("2010-01-04 09:30:02", "2010-01-04 09:30:06",
"2010-01-04 09:30:07", "2010-01-04 09:30:08", "2010-01-04 09:30:09",
"2010-01-04 09:30:10", "2010-01-04 09:30:11", "2010-01-04 09:30:13",
"2010-01-04 09:30:14")))
g <- seq(start(z), end(z), by = "2 sec")
na_locf(z, xout = g)
## 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))$mday == 5]
## this is the same as the last one except instead of always using the
## 5th of month in the result we show the date actually used
# idx has NAs wherever z.na does but has 1, 2, 3, ... instead of
# z.na's data values (so idx can be used for indexing)
idx <- coredata(na_locf(seq_along(z.na) + (0 * z.na)))
# pick off those elements of z.na that correspond to 5th
z.na[idx[as.POSIXlt(time(z.na))$mday == 5]]
## only fill single-day gaps
merge(z.na, filled1 = na_locf(z.na, maxgap = 1))
## fill NAs in first column by inflating the most recent non-NA
## by the growth in second column. Note that elements of x-x
## are NA if the corresponding element of x is NA and zero else
m <- zoo(cbind(c(1, 2, NA, NA, 5, NA, NA), seq(7)^2), as.Date(1:7))
r <- na_locf(m[,1]) * m[,2] / na_locf(m[,2] + (m[,1]-m[,1]))
cbind(V1 = r, V2 = m[,2])
## repeat a quarterly value every month
## preserving NAs
zq <- zoo(c(1, NA, 3, 4), as.yearqtr(2000) + 0:3/4)
tt <- as.yearmon(start(zq)) + seq(0, len = 3 * length(zq))/12
na_locf(zq, xout = tt, maxgap = 0)
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