Hi Bhaskar,
Perhaps you are looking for this:
approx(c(3,6,7),n=21)
$x
[1] 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 2.1 2.2 2.3 2.4 2.5 2.6 2.7
2.8
[20] 2.9 3.0
$y
[1] 3.0 3.3 3.6 3.9 4.2 4.5 4.8 5.1 5.4 5.7 6.0 6.1 6.2 6.3 6.4 6.5 6.6 6.7
6.8
[20] 6.9 7.0
This assumes that you are taking each value as a snapshot reading
rather than a cumulation of the values.
Jim
On Wed, Jun 9, 2021 at 4:33 AM Bhaskar Mitra <bhaskar.kolk...@gmail.com> wrote:
>
> Hello Everyone,
>
> I have data at weekly intervals.
> The data structure is something like this.
>
> df1 <-
> date a
> 1/7/2020 3
> 1/14/2020 6
> 1/21/2021 7
>
> I would like to convert the data from the weekly
> interval to the daily interval. Something like this.
>
> date a
> 1/7/2020 0.5
> 1/8/2020 0.3
> 1/9/2020 0.7
>
>
> I am using the following codes
>
> d1 <- nrow(df1)
>
> df2 <- data.frame(matrix(NA, nrow = (d1)*7, ncol = 1)
>
> inc <- 0
> for (i in 1:nrow(df1)) {
> for (j in 1:7) {
> inc <- inc + 1
> df2[inc,1] <- df1[i,1]/7
> }
> }
> rm(df1)
>
>
>
> However, the sum of the daily values generated in df2 differ
> from the original value in the df1 data frame. There is a 1-2% discrepancy.
> I would appreciate it if someone could suggest how to improve the codes.
>
> Thanks,
> Bhaskar
>
> [[alternative HTML version deleted]]
>
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