about interpolating data in r

On 22 Jul 2016, at 01:54, lily li <chocold12 at gmail.com> wrote:

Thanks, I meant if there are missing data at the beginning and end of a
dataframe, how to interpolate according to available data?

For example, the A column has missing values at the beginning and end, how
to interpolate linearly between 10 and 12 for the missing values?

df <- data.frame(A=c(NA, NA,10,11,12, NA),B=c(5,5,4,3,4,5),C=c(3.3,4,3,1.5,
2.2,4),time=as.Date(c("1990-01-01","1990-02-
07","1990-02-14","1990-02-28","1990-03-01","1990-03-20")))

On Thu, Jul 21, 2016 at 4:48 PM, William Dunlap <wdunlap at tibco.com> wrote:

Try approx(), as in:

df <-
data.frame(A=c(10,11,12),B=c(5,5,4),C=c(3.3,4,3),time=as.Date(c("1990-01-01","1990-02-07","1990-02-14")))
with(df, approx(x=time, y=C, xout=seq(min(time), max(time), by="days")))

Do you notice how one can copy and paste that example out of the
mail an into R to see how it works?  It would help if your questions
had that same property - show how the example data could be created.


Bill Dunlap
TIBCO Software
wdunlap tibco.com

On Thu, Jul 21, 2016 at 3:34 PM, lily li <chocold12 at gmail.com> wrote:

I have a question about interpolating missing values in a dataframe. The
dataframe is in the following, Column C has no data before 2009-01-05 and
after 2009-12-31, how to interpolate data for the blanks? That is to say,
interpolate linearly between these two gaps using 5.4 and 6.1? Thanks.


df
time                A      B     C
2009-01-01    3      4.5
2009-01-02    4      5
2009-01-03    3.3   6
2009-01-04    4.1   7
2009-01-05    4.4   6.2   5.4
...

2009-11-20    5.1   5.5   6.1
2009-11-21    5.4   4
...
2009-12-31    4.5   6

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