Combine two dataframe with different row number and interpolation between values

df3 = merge(df1, df2, all = TRUE)

Can I interest you in the join functions in dplyr?
https://www.datasciencemadesimple.com/join-in-r-merge-in-r/

Filling in missing data is a useful practice when the fake (simulated)
data is a small proportion of all data. When 2/3 of the data is fake one
must wonder if anything based on those numbers is real or an artifact of
assumptions made to generate the numbers.

I deal with weather data and some weather stations are set up to average
measurements between recorded values and others take a single reading at
regular intervals. How you interpolate might depend on which option
describes your data. The alternative is to use the method for recording ws
and apply it to the other data that will be merged with these data. I
assume there is more data, otherwise I see little point in expanding these
values out.

Tim

-----Original Message-----
From: R-help <r-help-bounces at r-project.org> On Behalf Of javad bayat
Sent: Wednesday, August 31, 2022 2:09 AM
To: r-help at r-project.org
Subject: [R] Combine two dataframe with different row number and
interpolation between values

[External Email]

 Dear all,
I am trying to combine two large dataframe in order to make a dataframe
with exactly the dimension of the second dataframe.
The first df is as follows:

df1 = data.frame(y = rep(c(2010,2011,2012,2013,2014), each = 2920), d =
rep(c(1:365,1:365,1:365,1:365,1:365),each=8),
      h = rep(c(seq(3,24, by = 3),seq(3,24, by = 3),seq(3,24, by =
3),seq(3,24, by = 3),seq(3,24, by = 3)),365),
      ws = rnorm(1:14600, mean=20))

head(df1)

     y       d   h        ws
1  2010  1  3     20.71488
2  2010  1  6     19.70125
3  2010  1  9     21.00180
4  2010  1 12     20.29236
5  2010  1 15     20.12317
6  2010  1 18     19.47782

The data in the "ws" column were measured with 3 hours frequency and I
need data with one hour frequency. I have made a second df as follows with
one hour frequency for the "ws" column.

df2 = data.frame(y = rep(c(2010,2011,2012,2013,2014), each = 8760), d =
rep(c(1:365,1:365,1:365,1:365,1:365),each=24),
      h = rep(c(1:24,1:24,1:24,1:24,1:24),365), ws = "NA")

head(df2)

      y      d    h   ws
1  2010  1    1   NA
2  2010  1    2   NA
3  2010  1    3   NA
4  2010  1    4   NA
5  2010  1    5   NA
6  2010  1    6   NA

What I am trying to do is combine these two dataframes so as to the rows in
df1 (based on the values of "y", "d", "h" columns) that have values
exactly similar to df2's rows copied in its place in the new df (df3).
For example, in the first dataframe the first row was measured at 3
o'clock on the first day of 2010 and this row must be placed on the third
row of the second dataframe which has a similar value (2010, 1, 3). Like
the below
table:
      y      d    h   ws
1  2010  1    1   NA
2  2010  1    2   NA
3  2010  1    3   20.71488
4  2010  1    4   NA
5  2010  1    5   NA
6  2010  1    6   19.70125

But regarding the values of the "ws" column for df2 that do not have value
(at 4 and 5 o'clock), I need to interpolate between the before and after
values to fill in the missing data of the "ws".
I have tried the following codes but they did not work correctly.

df3 = merge(df1, df2, by = "y")

Error: cannot allocate vector of size 487.9 Mb or

library(dplyr)
df3<- df1%>% full_join(df2)

Is there any way to do this?
Sincerely





--
Best Regards
Javad Bayat
M.Sc. Environment Engineering
Alternative Mail: bayat194 at yahoo.com

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