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Convert daily data to weekly data

6 messages · Miluji Sb, PIKAL Petr, jim holtman

#
Dear all,

I have daily data in wide-format from 01/01/1986 to 31/12/2016 by ID. I
would like to convert this to weekly average data. The data has been
generated by an algorithm.

I know that I can use the lubridate package but that would require me to
first convert the data to long-form (which is what I want). I am at a bit
of loss of how to extract the date from the variable names and then
converting the data to weekly average. Any help will be high appreciated.

### data
structure(list(X1986.01.01.10.30.00 = c(16.8181762695312, 16.8181762695312,
18.8294372558594, 16.8181762695312, 18.8294372558594, 16.835693359375
), X1986.01.02.10.30.00 = c(16.2272033691406, 16.2272033691406,
18.0772094726562, 16.2272033691406, 18.0772094726562, 16.2159423828125
), X1986.01.03.10.30.00 = c(15.8944396972656, 15.8944396972656,
17.7444152832031, 15.8944396972656, 17.7444152832031, 15.91943359375
), X1986.01.04.10.30.00 = c(16.2752380371094, 16.2752380371094,
18.125244140625, 16.2752380371094, 18.125244140625, 16.3352355957031
), X1986.01.05.10.30.00 = c(15.3706359863281, 15.3706359863281,
17.2806396484375, 15.3706359863281, 17.2806396484375, 15.3556213378906
), X1986.01.06.10.30.00 = c(15.3798828125, 15.3798828125, 17.3136291503906,
15.3798828125, 17.3136291503906, 15.4974060058594), ID = 1:6), .Names =
c("X1986.01.01.10.30.00",
"X1986.01.02.10.30.00", "X1986.01.03.10.30.00", "X1986.01.04.10.30.00",
"X1986.01.05.10.30.00", "X1986.01.06.10.30.00", "ID"), row.names = c(NA,
6L), class = "data.frame")

Sincerely,

Milu
#
Hi

Based on your explanation I would advice to use

?cut.POSIXt

with breaks "week". However your data are rather strange, you have data frame with names which looks like dates

names(test)
[1] "X1986.01.01.10.30.00" "X1986.01.02.10.30.00" "X1986.01.03.10.30.00"
[4] "X1986.01.04.10.30.00" "X1986.01.05.10.30.00" "X1986.01.06.10.30.00"
[7] "ID"

and under each name you have 6 numeric values
test[,1]
[1] 16.81818 16.81818 18.82944 16.81818 18.82944 16.83569

You (probably) can get dates by
as.Date(substring(names(test),2,11), format="%Y.%m.%d")
[1] "1986-01-01" "1986-01-02" "1986-01-03" "1986-01-04" "1986-01-05"
[6] "1986-01-06" NA

but if you want just average those 6 values below each date you could do

colMeans(test)

and/or bind it together.
ddd     aver
X1986.01.01.10.30.00 1986-01-01 17.49152
X1986.01.02.10.30.00 1986-01-02 16.84200
X1986.01.03.10.30.00 1986-01-03 16.51526
X1986.01.04.10.30.00 1986-01-04 16.90191
X1986.01.05.10.30.00 1986-01-05 16.00480
X1986.01.06.10.30.00 1986-01-06 16.04405
ID                         <NA>  3.50000

Cheers
Petr

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#
Dear Petr,

Thanks for your reply and the solution. The example dataset contains data
for the first six days of the year 1986. "X1986.01.01.10.30.00" is 01
January 1986 and the rest of the variable is redundant information. The
last date is given as "X2016.12.31.10.30.00".

I realized that I missed one information in my previous email, I would like
to compute the weekly average by the variable ID. Thanks again!

Sincerely,

Shouro
On Tue, May 29, 2018 at 3:24 PM, PIKAL Petr <petr.pikal at precheza.cz> wrote:

            

  
  
#
try this:
16.8181762695312,
+                                              18.8294372558594, 16 ....
[TRUNCATED]
+   group_by(ID, week) %>%
+   summarise(avg = mean(value))
# A tibble: 6 x 3
# Groups:   ID [?]
     ID  week   avg
  <int> <dbl> <dbl>
1     1    1.  16.0
2     2    1.  16.0
3     3    1.  17.9
4     4    1.  16.0
5     5    1.  17.9
6     6    1.  16.0
Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
On Tue, May 29, 2018 at 7:02 AM, Miluji Sb <milujisb at gmail.com> wrote:

            

  
  
#
Forgot the year if you also want to summarise by that.
16.8181762695312,
+                                              18.8294372558594, 16 ....
[TRUNCATED]
+   group_by(ID, year, week) %>%
+   summarise(avg = mean(value))
# A tibble: 6 x 4
# Groups:   ID, year [?]
     ID  year  week   avg
  <int> <dbl> <dbl> <dbl>
1     1 1986.    1.  16.0
2     2 1986.    1.  16.0
3     3 1986.    1.  17.9
4     4 1986.    1.  16.0
5     5 1986.    1.  17.9
6     6 1986.    1.  16.0



Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.
On Tue, May 29, 2018 at 7:02 AM, Miluji Sb <milujisb at gmail.com> wrote:

            

  
  
#
Dear Jim,

Thank you so much. The code works perfectly and is very fast for the large
amounts of data that I am processing!

Thanks again!

Sincerely,

Shouro
On Tue, May 29, 2018 at 11:50 PM, jim holtman <jholtman at gmail.com> wrote: