na.approx
Replace NA by Interpolation
Generic functions for replacing each NA
with interpolated
values.
- Keywords
- ts
Usage
na.approx(object, ...)
## S3 method for class 'zoo':
na.approx(object, x = index(object), xout, ..., na.rm = TRUE, along)
## S3 method for class 'zooreg':
na.approx(object, \dots)
## S3 method for class 'ts':
na.approx(object, \dots)
## S3 method for class 'default':
na.approx(object, x = index(object), xout, ..., na.rm = TRUE, maxgap = Inf, along)
na.spline(object, ...)
## S3 method for class 'zoo':
na.spline(object, x = index(object), xout, ..., na.rm = TRUE, along)
## S3 method for class 'zooreg':
na.spline(object, \dots)
## S3 method for class 'ts':
na.spline(object, \dots)
## S3 method for class 'default':
na.spline(object, x = index(object), xout, ..., na.rm = TRUE, maxgap = Inf, along)
Arguments
- object
- object in which
NA
s are to be replaced - x, xout
- Variables to be used for interpolation as in
approx
. - na.rm
- logical. Should leading
NA
s be removed? - maxgap
- maximum number of consecutive
NA
s to fill. Any longer gaps will be left unchanged. Note that all methods listed above can acceptmaxgap
as it is ultimately passed to thedefault
method. - along
- deprecated.
- ...
- further arguments passed to methods. The
n
argument ofapprox
is currently not supported.
Details
Missing values (NA
s) are replaced by linear interpolation via
approx
or cubic spline interpolation via spline
,
respectively.
It can also be used for series disaggregation by specifying xout
.
By default the index associated with object
is used
for interpolation. Note, that if this calls index.default
this gives an equidistant spacing 1:NROW(object)
. If object
is a matrix or data.frame, the interpolation is done separately for
each column.
If obj
is a plain vector then na.approx(obj, x, y, xout, ...)
returns approx(x = x[!na], y = coredata(obj)[!na], xout = xout, ...)
(where na
indicates observations with NA
) such that xout
defaults to x
.
If obj
is a zoo
, zooreg
or ts
object its
coredata
value is processed as described and its time index is xout
if
specified and index(obj)
otherwise. If obj
is two dimensional
then the above is applied to each column separately. For examples, see below.
If obj
has more than one column, the above strategy is applied to
each column.
Value
- An object of similar structure as
object
with (internal)NA
s replaced by interpolation. Leading or trailingNA
s are omitted ifna.rm = TRUE
or not replaced ifna.rm = FALSE
.
See Also
zoo
, approx
, na.contiguous
,
na.locf
, na.omit
, na.trim
, spline
,
stinterp
Examples
z <- zoo(c(2, NA, 1, 4, 5, 2), c(1, 3, 4, 6, 7, 8))
## use underlying time scale for interpolation
na.approx(z)
## use equidistant spacing
na.approx(z, 1:6)
# with and without na.rm = FALSE
zz <- c(NA, 9, 3, NA, 3, 2)
na.approx(zz, na.rm = FALSE)
na.approx(zz)
d0 <- as.Date("2000-01-01")
z <- zoo(c(11, NA, 13, NA, 15, NA), d0 + 1:6)
# NA fill, drop or keep leading/trailing NAs
na.approx(z)
na.approx(z, na.rm = FALSE)
# extrapolate to point outside of range of time points
# (a) drop NA, (b) keep NA, (c) extrapolate using rule = 2 from approx()
na.approx(z, xout = d0 + 7)
na.approx(z, xout = d0 + 7, na.rm = FALSE)
na.approx(z, xout = d0 + 7, rule = 2)
# use splines - extrapolation handled differently
z <- zoo(c(11, NA, 13, NA, 15, NA), d0 + 1:6)
na.spline(z)
na.spline(z, na.rm = FALSE)
na.spline(z, xout = d0 + 1:6)
na.spline(z, xout = d0 + 2:5)
na.spline(z, xout = d0 + 7)
na.spline(z, xout = d0 + 7, na.rm = FALSE)
## using na.approx for disaggregation
zy <- zoo(1:3, 2000:2001)
# yearly to monthly series
zmo <- na.approx(zy, xout = as.yearmon(2000+0:13/12))
zmo
# monthly to daily series
sq <- seq(as.Date(start(zmo)), as.Date(end(zmo), frac = 1), by = "day")
zd <- na.approx(zmo, x = as.Date, xout = sq)
head(zd)
# weekly to daily series
zww <- zoo(1:3, as.Date("2001-01-01") + seq(0, length = 3, by = 7))
zww
zdd <- na.approx(zww, xout = seq(start(zww), end(zww), by = "day"))
zdd
# The lines do not show up because of the NAs
plot(cbind(z, z), type = "b", screen = 1)
# use na.approx to force lines to appear
plot(cbind(z, na.approx(z)), type = "b", screen = 1)
# Workaround where less than 2 NAs can appear in a column
za <- zoo(cbind(1:5, NA, c(1:3, NA, 5), NA)); za
ix <- colSums(!is.na(za)) > 0
za[, ix] <- na.approx(za[, ix]); za
# using na.approx to create regularly spaced series
# z has points at 10, 20 and 40 minutes while output also has a point at 30
if(require("chron")) {
tt <- as.chron("2000-01-01 10:00:00") + c(1, 2, 4) * as.numeric(times("00:10:00"))
z <- zoo(1:3, tt)
tseq <- seq(start(z), end(z), by = times("00:10:00"))
na.approx(z, xout = tseq)
}