Spliting df into groups according to months for several years

I have longterm daily data of Precipitation for several stations. I would like to build the monthly sum and separate them into cold period (Nov-Apr) and warm period (May-Oct) for several years.

I have tried it as shown below and got to a result. unfortunately the data does not have the month in the date any more.. So if I plot it for every year I have 6 points rather than contiuos data..

how could I reinsert the months to the date?
Or is there a better approach than mine?

p.data <- read.csv (File, header = T, sep = ";", skip = 0, dec = ",")

p.data$Date <- as.POSIXct (p.data$Date, format = "%d.%m.%Y")

x = strptime(p.data$Date, '%Y-%m-%d ')
p.data$Month <- month(x)

##Cold and warm period, monthly sums
p.month.list <- split(p.data, p.data$Month)

jan <- setDT(p.month.list$`1`) [, lapply(.SD, sum), by =, (year(Date))]

feb <- setDT(p.month.list$`2`) [, lapply(.SD, sum), by =, (year(Date))]

mar <- setDT(p.month.list$`3`) [, lapply(.SD, sum), by =, (year(Date))]

apr <- setDT(p.month.list$`4`) [, lapply(.SD, sum), by =, (year(Date))]

may <- setDT(p.month.list$`5`) [, lapply(.SD, sum), by =, (year(Date))]

jun <- setDT(p.month.list$`6`) [, lapply(.SD, sum), by =, (year(Date))]

jul <- setDT(p.month.list$`7`) [, lapply(.SD, sum), by =, (year(Date))]

aug <- setDT(p.month.list$`8`) [, lapply(.SD, sum), by =, (year(Date))]

sep <- setDT(p.month.list$`9`) [, lapply(.SD, sum), by =, (year(Date))]

oct <- setDT(p.month.list$`10`) [, lapply(.SD, sum), by =, (year(Date))]

nov <- setDT(p.month.list$`11`) [, lapply(.SD, sum), by =, (year(Date))]

dec <- setDT(p.month.list$`12`) [, lapply(.SD, sum), by =, (year(Date))]


p.cold <- rbind(nov, dec, jan, feb, mar, apr)
p.cold <- p.cold[order(p.cold$year)]

p.warm <- rbind(may, jun, jul, aug, sep, oct)
p.warm <- p.warm[order(p.warm$year)]

Hello.
Thanks for providing code , but you could take further steps to make it more convenient for other forum users to help you.

Share some representative data that will enable your code to run and show the problematic behaviour. In your case this would be p.data in its state immediately after your use of as.POSIXct

You might use tools such as the library datapasta, or the base function dput() to share a portion of data in code form, i.e. that can be copied from forum and pasted to R session.

Reprex Guide

Hi thank you for trying to help me!

I have not managed to figure out data.pasta this quickly but i can send the out put of dput()

1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 

EDIT - redacted the above to spare the thread leangth

Is this what you were asking for?

unfortunately I cant use that.
the result of dput() should begin
structure(list(
I'm guessing you tried to copy and paste but didnt grab the start.

These are head and tail after POSIX:
> head(p.data)
       Date Vienna.Rathaus Hainburg.Bad.Deutsch.Altenburg Seidendorf.Klopein Kirchbichel.Hopfgarten
1 1971-01-01              0                            0.0                2.8                    0.0
2 1971-01-02              0                            1.1               11.2                    1.6
3 1971-01-03              8                            6.2                1.2                    2.2
4 1971-01-04              0                            0.2                0.0                    0.0
5 1971-01-05              0                            0.0                0.0                    0.0
6 1971-01-06              0                            0.0                0.0                    0.0
 Schaerding.Rossbach Deutsch.Brodersdorf Angern.Baumgarten Spielefeld.Strasz Salzburg.Galnegg Diepoldsau.Hohenems.
1                 0.0                   0                NA                NA              1.0                  0.4
2                 0.2                   0                NA                NA              2.0                  0.0
3                 0.0                   0                NA                NA              2.8                  0.0
4                 0.0                   0                NA                NA              0.0                  0.0
5                 0.0                   0                NA                NA              0.0                  0.0
6                 0.0                   0                NA                NA              0.0                  0.0
 Lustenau.Gaissau. Engelhartszell.Pfarrkirchen. Month
1                 0                          2.1     1
2                 0                          0.0     1
3                 0                          0.0     1
4                 0                          0.0     1
5                 0                          0.0     1
6                 0                          0.0     1
> tail(p.data)
           Date Vienna.Rathaus Hainburg.Bad.Deutsch.Altenburg Seidendorf.Klopein Kirchbichel.Hopfgarten
17527 2018-12-26              0                            5.8                  0                    0.0
17528 2018-12-27              0                            0.4                  0                    0.0
17529 2018-12-28              1                            0.0                  0                    0.0
17530 2018-12-29              2                            0.0                  0                    2.8
17531 2018-12-30              3                            0.4                  0                    8.3
17532 2018-12-31              0                            3.1                  0                   14.8
     Schaerding.Rossbach Deutsch.Brodersdorf Angern.Baumgarten Spielefeld.Strasz Salzburg.Galnegg Diepoldsau.Hohenems.
17527                 0.0                 0.0               0.0                 0              0.0                  0.0
17528                 0.0                 0.0               0.0                 0              0.0                  0.0
17529                 0.0                 0.0               0.0                 0              1.5                  0.0
17530                 5.0                 0.1               0.6                 0              7.3                  1.7
17531                 1.0                 0.8               3.3                 0             11.2                  3.4
17532                 3.2                 0.0               0.3                 0             30.7                  3.8
     Lustenau.Gaissau. Engelhartszell.Pfarrkirchen. Month
17527               0.0                          0.0    12
17528               0.0                          0.5    12
17529               0.0                          0.0    12
17530               1.2                         10.2    12
17531               7.5                          7.4    12
17532               3.0                          6.6    12

unfortunately I can not see the start.. it seems to be too lang..

I have made a shorter sample now.

 dput(p.data[1:20,])
structure(list(Date = structure(c(31532400, 31618800, 31705200, 
31791600, 31878000, 31964400, 32050800, 32137200, 32223600, 32310000, 
32396400, 32482800, 32569200, 32655600, 32742000, 32828400, 32914800, 
33001200, 33087600, 33174000), class = c("POSIXct", "POSIXt"), tzone = ""), 
    Vienna.Rathaus = c(0, 0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 4.8), Hainburg.Bad.Deutsch.Altenburg = c(0, 
    1.1, 6.2, 0.2, 0, 0, 0, 0, 0.1, 0.3, 0, 0, 0, 0, 0, 0, 0.1, 
    0.1, 0.3, 0.2), Seidendorf.Klopein = c(2.8, 11.2, 1.2, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.8, 10.4, 0, 0, 0, 4.5), Kirchbichel.Hopfgarten = c(0, 
    1.6, 2.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    1.1), Schaerding.Rossbach = c(0, 0.2, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4), Deutsch.Brodersdorf = c(0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), 
    Angern.Baumgarten = c(NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_), Spielefeld.Strasz = c(NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
    NA_real_), Salzburg.Galnegg = c(1, 2, 2.8, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5), Diepoldsau.Hohenems. = c(0.4, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.5
    ), Lustenau.Gaissau. = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0, 0, 0, 0, 0, 0, 0.8, 4.2, 1.8), Engelhartszell.Pfarrkirchen. = c(2.1, 
    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.2, 0, 0, 0, 0.4, 
    0.2), Month = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
    1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L)), row.names = c(NA, 20L
), class = "data.frame")

Sorry for the spam.

Just in case the one befor was to short:

dput(p.data[1:200,])
structure(list(Date = structure(c(31532400, 31618800, 31705200, 
31791600, 31878000, 31964400, 32050800, 32137200, 32223600, 32310000, 
32396400, 32482800, 32569200, 32655600, 32742000, 32828400, 32914800, 
33001200, 33087600, 33174000, 33260400, 33346800, 33433200, 33519600, 
33606000, 33692400, 33778800, 33865200, 33951600, 34038000, 34124400, 
34210800, 34297200, 34383600, 34470000, 34556400, 34642800, 34729200, 
34815600, 34902000, 34988400, 35074800, 35161200, 35247600, 35334000, 
35420400, 35506800, 35593200, 35679600, 35766000, 35852400, 35938800, 
36025200, 36111600, 36198000, 36284400, 36370800, 36457200, 36543600, 
36630000, 36716400, 36802800, 36889200, 36975600, 37062000, 37148400, 
37234800, 37321200, 37407600, 37494000, 37580400, 37666800, 37753200, 
37839600, 37926000, 38012400, 38098800, 38185200, 38271600, 38358000, 
38444400, 38530800, 38617200, 38703600, 38790000, 38876400, 38962800, 
39049200, 39135600, 39222000, 39308400, 39394800, 39481200, 39567600, 
39654000, 39740400, 39826800, 39913200, 39999600, 40086000, 40172400, 
40258800, 40345200, 40431600, 40518000, 40604400, 40690800, 40777200, 
40863600, 40950000, 41036400, 41122800, 41209200, 41295600, 41382000, 
41468400, 41554800, 41641200, 41727600, 41814000, 41900400, 41986800, 
42073200, 42159600, 42246000, 42332400, 42418800, 42505200, 42591600, 
42678000, 42764400, 42850800, 42937200, 43023600, 43110000, 43196400, 
43282800, 43369200, 43455600, 43542000, 43628400, 43714800, 43801200, 
43887600, 43974000, 44060400, 44146800, 44233200, 44319600, 44406000, 
44492400, 44578800, 44665200, 44751600, 44838000, 44924400, 45010800, 
45097200, 45183600, 45270000, 45356400, 45442800, 45529200, 45615600, 
45702000, 45788400, 45874800, 45961200, 46047600, 46134000, 46220400, 
46306800, 46393200, 46479600, 46566000, 46652400, 46738800, 46825200, 
46911600, 46998000, 47084400, 47170800, 47257200, 47343600, 47430000, 
47516400, 47602800, 47689200, 47775600, 47862000, 47948400, 48034800, 
48121200, 48207600, 48294000, 48380400, 48466800, 48553200, 48639600, 
48726000), class = c("POSIXct", "POSIXt"), tzone = ""), Vienna.Rathaus = c(0, 
0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4.8, 0, 
0, 0, 0, 0, 0, 1.4, 0, 0, 0, 0, 3.7, 0, 2.5, 0.8, 0, 0, 0, 0, 
0.2, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 1.1, 0, 3.3, 0.6, 0.7, 2.8, 
0.3, 1.5, 6.5, 0.6, 0.5, 0.5, 0, 0, 4.8, 0, 0, 0, 0, 0, 1.1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 34.4, 0, 0, 4.5, 9.8, 0, 0, 4.9, 0, 
0, 0, 2.3, 0, 0, 2, 0, 0, 0, 0, 2.3, 0, 0, 0, 0, 0, 0, 1.7, 0, 
0, 0, 0, 0, 0, 4.6, 0.7, 0.3, 1.2, 0.1, 0, 0, 11.5, 0, 0, 0, 
3, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 1.4, 0, 0, 10.3, 0.4, 3.3, 18.7, 0, 0, 0, 0, 0, 0, 0, 1.2, 
21, 2.2, 0.6, 0, 1.2, 0, 1.4, 0, 37, 3.1, 0, 1.3, 0, 2.8, 0, 
0, 0, 1.1, 0, 1.6, 3.8, 3.6, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
1.2, 0, 0, 0, 0, 8.3, 0), Hainburg.Bad.Deutsch.Altenburg = c(0, 
1.1, 6.2, 0.2, 0, 0, 0, 0, 0.1, 0.3, 0, 0, 0, 0, 0, 0, 0.1, 0.1, 
0.3, 0.2, 2.2, 0.9, 0, 0, 0, 0, 0.3, 0, 0, 0, 0, 0.9, 0, 2.5, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.2, 1.2, 3.7, 0, 0, 0, 0, 0.3, 
0, 0.2, 1.1, 0.9, 1.4, 11.7, 0.4, 0.5, 0, 0, 2.5, 2.1, 0.9, 0, 
0.4, 0.2, 0.4, 0.2, 0.1, 0, 0, 0, 0, 0, 0, 0, 0.3, 18.3, 0.2, 
0.2, 2.6, 15.8, 0.2, 0, 0, 4.4, 0.4, 1.8, 0.4, 0, 5.2, 3.6, 0, 
0, 0, 0, 0, 0, 0, 3.1, 0, 0, 0, 3.6, 0, 0, 0, 0, 0, 0, 10.7, 
2.1, 1.6, 0.4, 0, 0, 1.7, 2.7, 0, 0.3, 0, 0.7, 0.8, 0, 0, 0, 
0.1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.1, 1.1, 0, 0, 0, 0, 3.7, 
0, 0, 1.9, 2.1, 1.9, 11.8, 0, 0, 0, 0, 0, 0, 1.9, 0.5, 14.6, 
18.1, 0.1, 0, 2.1, 0, 0, 0.3, 11.8, 4.2, 0, 0.7, 0, 13.9, 0.2, 
0, 0, 1.3, 0.9, 0.2, 4.2, 3.4, 0.9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0.3, 0, 0, 13.2, 0), Seidendorf.Klopein = c(2.8, 11.2, 
1.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.8, 10.4, 0, 0, 0, 4.5, 
12.2, 4.3, 0, 2.5, 0, 0, 3, 0, 0, 0, 9, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 24.5, 3.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 6.2, 3.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6.2, 2.8, 
0, 8.5, 0, 0, 10.5, 0, 0, 7.5, 4.4, 4.6, 0, 2.6, 0, 0, 8, 4, 
1, 11, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
0, 2.6, 3, 2.2, 0, 22, 0, 10.2, 4.8, 2.6, 4.6, 0, 6.2, 0, 0, 
0, 0, 2.4, 3.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 22.2, 26.2, 10.2, 2.2, 3.6, 0, 0, 0, 0, 2.6, 8.4, 2.8, 
2.4, 0, 2.6, 2.4, 2.2, 1.2, 1.4, 0, 0, 0, 0, 0, 0, 0, 2.4, 0, 
0, 3.6, 2.8, 0, 8.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 31.8, 
0, 0, 0, 3.8, 3.2, 0), Kirchbichel.Hopfgarten = c(0, 1.6, 2.2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.1, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 8.2, 0, 18, 1.3, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 5.1, 0, 8, 0, 0, 5.8, 1, 1, 4, 19, 0.5, 6.1, 20.7, 1.5, 
4.9, 1.1, 0, 0, 0, 0, 1.2, 0, 0, 0, 1.1, 10.5, 0.9, 0, 0, 0, 
5.7, 0, 0, 0, 0, 0, 9.4, 0, 0, 7.5, 5.2, 3, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 2.1, 0, 0, 0, 0, 0, 0, 5.2, 0, 0, 0, 0, 
0, 0, 7, 0, 0, 13.4, 0, 0, 0, 0, 1.5, 14, 0, 0.7, 0, 0, 0, 0, 
16.2, 0, 0, 1.7, 1.4, 1.2, 0, 0, 0, 15.2, 1.5, 2.7, 2.5, 0.9, 
0, 0, 0, 2.5, 19.5, 12.5, 10.4, 8, 0, 0, 25, 4.4, 3.1, 4, 9.6, 
4.4, 0, 3.3, 17.1, 0, 1, 0, 11.8, 0, 5.2, 1.8, 16.2, 3.4, 0, 
1.6, 0, 7.2, 0, 4.2, 4.3, 6, 4.5, 6.3, 3.2, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 4.7, 14.8, 0, 0, 0, 1.9, 23, 0), Schaerding.Rossbach = c(0, 
0.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 
0, 0, 0, 1.3, 0, 0.2, 0, 0, 0, 0, 0, 9.5, 0, 5.8, 0, 0, 0.4, 
0.3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.5, 0, 0, 0, 2.3, 3.9, 3.7, 
1.3, 4, 0, 0, 1.6, 0, 0.3, 0, 0.3, 0, 3, 3.6, 0, 3.4, 0, 0.5, 
0.4, 0, 0, 0, 3.1, 0, 0, 0, 0, 0, 9, 0.3, 0.4, 0.5, 4.7, 0, 0, 
0, 0, 0, 0, 0, 0, 0.2, 6.9, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 
4.9, 0, 0, 0, 0, 0, 0, 9.2, 6.7, 2.8, 20.5, 0, 0, 0, 2.5, 1.5, 
2.6, 0, 0, 0, 0, 0, 0.2, 2, 0, 0, 0.6, 0.4, 0, 0, 0, 0, 9, 0, 
0, 0, 2.7, 11.7, 0, 0, 0, 3, 6, 2.5, 5.1, 6.7, 0, 2, 0, 0, 6, 
0, 14.4, 0, 6, 7.4, 1, 1.2, 0, 8.1, 0, 0.2, 3.2, 18, 2, 0, 0.4, 
0, 0, 0, 4.5, 0, 3.2, 0.2, 1.8, 2.6, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 12.2, 0, 0, 0, 0.8, 17, 0), Deutsch.Brodersdorf = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.8, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 2.8, 2, 0, 0, 0, 1.4, 0.6, 0, 0, 2.2, 8.5, 0, 6, 
0, 0.4, 0.3, 0, 0, 6.8, 0, 0, 0, 0, 2.4, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 27.5, 0, 0, 6.8, 8, 0, 0, 1, 0, 0.8, 0.6, 1.8, 0, 2, 
4.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.2, 0, 0, 0, 
6.5, 0, 0, 0, 1.5, 0, 4.8, 2.8, 0, 0.8, 0, 1, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.2, 0, 0, 0, 0, 3.5, 0, 10.5, 
3, 0, 14.4, 7.5, 0, 0, 0, 0, 8.2, 0, 0, 5.5, 20.4, 6.8, 0, 0, 
0, 0, 0.3, 0, 38.2, 0, 0, 0, 0, 17.8, 0, 0, 0, 4.8, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.8, 0, 0, 0, 0, 7.8, 0), Angern.Baumgarten = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_), Spielefeld.Strasz = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_), Salzburg.Galnegg = c(1, 2, 2.8, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.6, 
0, 1, 0, 0, 0, 0, 0, 0, 0, 9.4, 0, 11.5, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 2, 0, 2, 0, 0, 13, 0, 0, 10.5, 13.4, 0, 11.6, 18.8, 
2, 4.5, 3, 0, 2.5, 2, 1.5, 0, 0, 0, 0, 2.2, 6, 2.2, 0, 0, 0, 
6.5, 0, 0, 0, 0, 0, 19, 1, 0, 7.8, 12.6, 7.4, 1.2, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 8, 1, 0, 0, 0, 0, 0, 7.5, 0, 0, 0, 0, 
0, 0, 11, 3.2, 0, 12, 0, 0, 0, 0, 3, 14, 0, 0, 0, 0, 0, 0, 3.5, 
0, 0, 0, 5.5, 0, 0, 0, 0, 16, 2.5, 0.5, 2, 3.5, 0, 0, 0, 1.5, 
24.5, 8.4, 7, 12.5, 0, 0, 0, 8.5, 1, 2.5, 14, 12.5, 1, 11.2, 
60, 4.5, 1.9, 0, 11.9, 3.5, 2.4, 6, 24.5, 25, 0, 0, 0, 5, 0, 
4.5, 0, 8, 5.5, 15, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 
0, 0, 0, 4.2, 24, 0), Diepoldsau.Hohenems. = c(0.4, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.5, 4.7, 0, 3.8, 
0, 0, 1.7, 0.8, 0, 0, 0, 0, 12.2, 1.6, 19.9, 1.1, 0.3, 0, 0, 
0, 0, 0, 0, 0, 0.9, 2.1, 0, 2.3, 1.3, 8.2, 8.8, 0, 3.1, 12.7, 
4.2, 0, 0, 13.2, 2.1, 7.4, 0.8, 1.7, 2.2, 0, 0, 0, 0, 0, 0, 3.1, 
6.2, 0.6, 0, 0, 7.2, 1.2, 0, 0, 0, 0, 0, 20.8, 5.5, 0, 0, 5.1, 
10.5, 0, 0, 0, 0, 0, 0, 0, 0, 1.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0.2, 3.7, 0, 0.9, 1.8, 0, 0, 0, 3.2, 0, 2.7, 29.5, 0.6, 0, 
1.4, 6.3, 4.2, 1.7, 6.8, 1.5, 0, 0, 0, 0, 0, 27, 1.8, 0, 0, 0, 
0, 0, 2.3, 0.8, 0, 2.3, 5.5, 4.6, 2.7, 3.3, 0.2, 0, 14.8, 0.9, 
15.5, 3.6, 0.4, 2.1, 0, 1.3, 2.3, 7.5, 47.5, 0, 7.1, 31.2, 7.2, 
8.3, 5.2, 0, 24.2, 0, 2.1, 3.4, 26.4, 0, 0, 6.2, 0, 8.6, 7.5, 
21.3, 0, 1.9, 4.2, 25.3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4.2, 
1.3, 0, 0, 0.8, 10.2, 21.3, 4.2), Lustenau.Gaissau. = c(0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.8, 4.2, 1.8, 0, 
2.1, 0, 0, 0.8, 3.5, 2, 0, 0, 0, 12.5, 2.4, 20.7, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0.5, 0.8, 0, 2.4, 2.3, 2, 5, 1.5, 3.4, 12.1, 2.3, 
0, 0, 13.7, 1.4, 6.9, 0, 0.3, 0.5, 0, 0, 0, 0, 0, 1, 4.9, 0.3, 
0.2, 0, 0, 3.5, 1.9, 0, 0, 0, 0, 0, 11.5, 0.4, 0, 6.8, 1.9, 9.6, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.3, 0, 0, 0, 5.8, 0, 0, 0, 0, 0, 
1, 8.2, 0, 1.3, 0, 0, 0, 0, 3.2, 0, 1.6, 27.2, 0, 0, 2.9, 11.1, 
1.8, 0.7, 3, 0, 0, 0, 0, 0, 0, 13.1, 0.7, 0, 0, 3.8, 0, 0, 0, 
0, 0, 3.9, 0.5, 6.8, 2.3, 0, 2.3, 2.6, 4.5, 0, 16, 4.9, 0, 0, 
0.2, 0.4, 1.5, 17.2, 43.1, 0, 5.6, 20.8, 4.5, 0, 0, 0.2, 25.6, 
0.3, 1.8, 11.5, 9.4, 0, 0, 0, 0, 5, 7.1, 22.2, 0, 3.8, 7, 18.7, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 30.2, 4.3, 0, 0, 3.3, 6.8, 20.5, 
3.2, 7.8), Engelhartszell.Pfarrkirchen. = c(2.1, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.2, 0, 0, 0, 0.4, 0.2, 0, 0, 0.4, 
0, 0, 1.4, 0.6, 1.4, 0, 0, 0, 12.5, 1.6, 11.8, 0, 0, 0, 0, 2.3, 
0, 0, 0, 0, 3.2, 8.4, 0, 0, 1.3, 0.4, 1.2, 0, 0, 4.2, 13.5, 12.6, 
21.3, 7.9, 16.8, 21.6, 2.4, 0.7, 8.6, 2.9, 0, 8.3, 12.4, 0, 6.5, 
11.3, 8.7, 0, 0.5, 0, 0, 1.2, 0, 0, 0, 0, 0, 7.8, 0, 0, 0, 6.8, 
0.3, 0.8, 1.3, 0.8, 0, 0, 1.2, 0, 0, 3.2, 0, 0, 0, 0, 0.6, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18.3, 14.2, 8.6, 11.2, 0, 
0, 0, 0, 3.8, 8.4, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 
0, 1.7, 0, 0, 0, 0, 0, 0, 0, 0, 6.1, 2.4, 8.2, 11.6, 7, 0, 0, 
0.9, 0, 81.3, 0, 27.3, 11.8, 4.9, 10.1, 8.7, 6.3, 0, 8.5, 0, 
0.6, 5.2, 18.8, 7.2, 0, 1.1, 0, 0, 0, 4.2, 8.6, 7.7, 0.9, 13.4, 
4, 0, 0, 0, 1.2, 0, 0, 0, 0, 0, 0, 0, 10.3, 0, 0, 2.1, 12.8, 
0, 0), Month = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L)), row.names = c(NA, 
200L), class = "data.frame")

I think I got the sample of my data:

structure(list(Date = structure(c(31532400, 31618800, 31705200, 
31791600, 31878000, 31964400, 32050800, 32137200, 32223600, 32310000, 
32396400, 32482800, 32569200, 32655600, 32742000, 32828400, 32914800, 
33001200, 33087600, 33174000, 33260400, 33346800, 33433200, 33519600, 
33606000, 33692400, 33778800, 33865200, 33951600, 34038000, 34124400, 
34210800, 34297200, 34383600, 34470000, 34556400, 34642800, 34729200, 
34815600, 34902000, 34988400, 35074800, 35161200, 35247600, 35334000, 
35420400, 35506800, 35593200, 35679600, 35766000, 35852400, 35938800, 
36025200, 36111600, 36198000, 36284400, 36370800, 36457200, 36543600, 
36630000, 36716400, 36802800, 36889200, 36975600, 37062000, 37148400, 
37234800, 37321200, 37407600, 37494000, 37580400, 37666800, 37753200, 
37839600, 37926000, 38012400, 38098800, 38185200, 38271600, 38358000, 
38444400, 38530800, 38617200, 38703600, 38790000, 38876400, 38962800, 
39049200, 39135600, 39222000, 39308400, 39394800, 39481200, 39567600, 
39654000, 39740400, 39826800, 39913200, 39999600, 40086000, 40172400, 
40258800, 40345200, 40431600, 40518000, 40604400, 40690800, 40777200, 
40863600, 40950000, 41036400, 41122800, 41209200, 41295600, 41382000, 
41468400, 41554800, 41641200, 41727600, 41814000, 41900400, 41986800, 
42073200, 42159600, 42246000, 42332400, 42418800, 42505200, 42591600, 
42678000, 42764400, 42850800, 42937200, 43023600, 43110000, 43196400, 
43282800, 43369200, 43455600, 43542000, 43628400, 43714800, 43801200, 
43887600, 43974000, 44060400, 44146800, 44233200, 44319600, 44406000, 
44492400, 44578800, 44665200, 44751600, 44838000, 44924400, 45010800, 
45097200, 45183600, 45270000, 45356400, 45442800, 45529200, 45615600, 
45702000, 45788400, 45874800, 45961200, 46047600, 46134000, 46220400, 
46306800, 46393200, 46479600, 46566000, 46652400, 46738800, 46825200, 
46911600, 46998000, 47084400, 47170800, 47257200, 47343600, 47430000, 
47516400, 47602800, 47689200, 47775600, 47862000, 47948400, 48034800, 
48121200, 48207600, 48294000, 48380400, 48466800, 48553200, 48639600, 
48726000), class = c("POSIXct", "POSIXt"), tzone = ""), Vienna.Rathaus = c(0, 
0, 8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4.8, 0, 
0, 0, 0, 0, 0, 1.4, 0, 0, 0, 0, 3.7, 0, 2.5, 0.8, 0, 0, 0, 0, 
0.2, 0, 0, 0, 0, 0, 0, 0.5, 0, 0, 0, 1.1, 0, 3.3, 0.6, 0.7, 2.8, 
0.3, 1.5, 6.5, 0.6, 0.5, 0.5, 0, 0, 4.8, 0, 0, 0, 0, 0, 1.1, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 34.4, 0, 0, 4.5, 9.8, 0, 0, 4.9, 0, 
0, 0, 2.3, 0, 0, 2, 0, 0, 0, 0, 2.3, 0, 0, 0, 0, 0, 0, 1.7, 0, 
0, 0, 0, 0, 0, 4.6, 0.7, 0.3, 1.2, 0.1, 0, 0, 11.5, 0, 0, 0, 
3, 0.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 1.4, 0, 0, 10.3, 0.4, 3.3, 18.7, 0, 0, 0, 0, 0, 0, 0, 1.2, 
21, 2.2, 0.6, 0, 1.2, 0, 1.4, 0, 37, 3.1, 0, 1.3, 0, 2.8, 0, 
0, 0, 1.1, 0, 1.6, 3.8, 3.6, 0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
1.2, 0, 0, 0, 0, 8.3, 0), Hainburg.Bad.Deutsch.Altenburg = c(0, 
1.1, 6.2, 0.2, 0, 0, 0, 0, 0.1, 0.3, 0, 0, 0, 0, 0, 0, 0.1, 0.1, 
0.3, 0.2, 2.2, 0.9, 0, 0, 0, 0, 0.3, 0, 0, 0, 0, 0.9, 0, 2.5, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.2, 1.2, 3.7, 0, 0, 0, 0, 0.3, 
0, 0.2, 1.1, 0.9, 1.4, 11.7, 0.4, 0.5, 0, 0, 2.5, 2.1, 0.9, 0, 
0.4, 0.2, 0.4, 0.2, 0.1, 0, 0, 0, 0, 0, 0, 0, 0.3, 18.3, 0.2, 
0.2, 2.6, 15.8, 0.2, 0, 0, 4.4, 0.4, 1.8, 0.4, 0, 5.2, 3.6, 0, 
0, 0, 0, 0, 0, 0, 3.1, 0, 0, 0, 3.6, 0, 0, 0, 0, 0, 0, 10.7, 
2.1, 1.6, 0.4, 0, 0, 1.7, 2.7, 0, 0.3, 0, 0.7, 0.8, 0, 0, 0, 
0.1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.1, 1.1, 0, 0, 0, 0, 3.7, 
0, 0, 1.9, 2.1, 1.9, 11.8, 0, 0, 0, 0, 0, 0, 1.9, 0.5, 14.6, 
18.1, 0.1, 0, 2.1, 0, 0, 0.3, 11.8, 4.2, 0, 0.7, 0, 13.9, 0.2, 
0, 0, 1.3, 0.9, 0.2, 4.2, 3.4, 0.9, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0.3, 0, 0, 13.2, 0), Seidendorf.Klopein = c(2.8, 11.2, 
1.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.8, 10.4, 0, 0, 0, 4.5, 
12.2, 4.3, 0, 2.5, 0, 0, 3, 0, 0, 0, 9, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 24.5, 3.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 6.2, 3.8, 0, 0, 0, 0, 0, 0, 0, 0, 0, 6.2, 2.8, 
0, 8.5, 0, 0, 10.5, 0, 0, 7.5, 4.4, 4.6, 0, 2.6, 0, 0, 8, 4, 
1, 11, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
0, 2.6, 3, 2.2, 0, 22, 0, 10.2, 4.8, 2.6, 4.6, 0, 6.2, 0, 0, 
0, 0, 2.4, 3.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 22.2, 26.2, 10.2, 2.2, 3.6, 0, 0, 0, 0, 2.6, 8.4, 2.8, 
2.4, 0, 2.6, 2.4, 2.2, 1.2, 1.4, 0, 0, 0, 0, 0, 0, 0, 2.4, 0, 
0, 3.6, 2.8, 0, 8.4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 31.8, 
0, 0, 0, 3.8, 3.2, 0), Kirchbichel.Hopfgarten = c(0, 1.6, 2.2, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.1, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 8.2, 0, 18, 1.3, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 5.1, 0, 8, 0, 0, 5.8, 1, 1, 4, 19, 0.5, 6.1, 20.7, 1.5, 
4.9, 1.1, 0, 0, 0, 0, 1.2, 0, 0, 0, 1.1, 10.5, 0.9, 0, 0, 0, 
5.7, 0, 0, 0, 0, 0, 9.4, 0, 0, 7.5, 5.2, 3, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 2.1, 0, 0, 0, 0, 0, 0, 5.2, 0, 0, 0, 0, 
0, 0, 7, 0, 0, 13.4, 0, 0, 0, 0, 1.5, 14, 0, 0.7, 0, 0, 0, 0, 
16.2, 0, 0, 1.7, 1.4, 1.2, 0, 0, 0, 15.2, 1.5, 2.7, 2.5, 0.9, 
0, 0, 0, 2.5, 19.5, 12.5, 10.4, 8, 0, 0, 25, 4.4, 3.1, 4, 9.6, 
4.4, 0, 3.3, 17.1, 0, 1, 0, 11.8, 0, 5.2, 1.8, 16.2, 3.4, 0, 
1.6, 0, 7.2, 0, 4.2, 4.3, 6, 4.5, 6.3, 3.2, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 4.7, 14.8, 0, 0, 0, 1.9, 23, 0), Schaerding.Rossbach = c(0, 
0.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.4, 
0, 0, 0, 1.3, 0, 0.2, 0, 0, 0, 0, 0, 9.5, 0, 5.8, 0, 0, 0.4, 
0.3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.5, 0, 0, 0, 2.3, 3.9, 3.7, 
1.3, 4, 0, 0, 1.6, 0, 0.3, 0, 0.3, 0, 3, 3.6, 0, 3.4, 0, 0.5, 
0.4, 0, 0, 0, 3.1, 0, 0, 0, 0, 0, 9, 0.3, 0.4, 0.5, 4.7, 0, 0, 
0, 0, 0, 0, 0, 0, 0.2, 6.9, 0, 0, 0, 0, 7, 0, 0, 0, 0, 0, 0, 
4.9, 0, 0, 0, 0, 0, 0, 9.2, 6.7, 2.8, 20.5, 0, 0, 0, 2.5, 1.5, 
2.6, 0, 0, 0, 0, 0, 0.2, 2, 0, 0, 0.6, 0.4, 0, 0, 0, 0, 9, 0, 
0, 0, 2.7, 11.7, 0, 0, 0, 3, 6, 2.5, 5.1, 6.7, 0, 2, 0, 0, 6, 
0, 14.4, 0, 6, 7.4, 1, 1.2, 0, 8.1, 0, 0.2, 3.2, 18, 2, 0, 0.4, 
0, 0, 0, 4.5, 0, 3.2, 0.2, 1.8, 2.6, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 12.2, 0, 0, 0, 0.8, 17, 0), Deutsch.Brodersdorf = c(0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.8, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 2.8, 2, 0, 0, 0, 1.4, 0.6, 0, 0, 2.2, 8.5, 0, 6, 
0, 0.4, 0.3, 0, 0, 6.8, 0, 0, 0, 0, 2.4, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 27.5, 0, 0, 6.8, 8, 0, 0, 1, 0, 0.8, 0.6, 1.8, 0, 2, 
4.2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1.2, 0, 0, 0, 
6.5, 0, 0, 0, 1.5, 0, 4.8, 2.8, 0, 0.8, 0, 1, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.2, 0, 0, 0, 0, 3.5, 0, 10.5, 
3, 0, 14.4, 7.5, 0, 0, 0, 0, 8.2, 0, 0, 5.5, 20.4, 6.8, 0, 0, 
0, 0, 0.3, 0, 38.2, 0, 0, 0, 0, 17.8, 0, 0, 0, 4.8, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2.8, 0, 0, 0, 0, 7.8, 0), Angern.Baumgarten = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_), Spielefeld.Strasz = c(NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
NA_real_, NA_real_, NA_real_), Salzburg.Galnegg = c(1, 2, 2.8, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0.6, 
0, 1, 0, 0, 0, 0, 0, 0, 0, 9.4, 0, 11.5, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 2, 0, 2, 0, 0, 13, 0, 0, 10.5, 13.4, 0, 11.6, 18.8, 
2, 4.5, 3, 0, 2.5, 2, 1.5, 0, 0, 0, 0, 2.2, 6, 2.2, 0, 0, 0, 
6.5, 0, 0, 0, 0, 0, 19, 1, 0, 7.8, 12.6, 7.4, 1.2, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 8, 1, 0, 0, 0, 0, 0, 7.5, 0, 0, 0, 0, 
0, 0, 11, 3.2, 0, 12, 0, 0, 0, 0, 3, 14, 0, 0, 0, 0, 0, 0, 3.5, 
0, 0, 0, 5.5, 0, 0, 0, 0, 16, 2.5, 0.5, 2, 3.5, 0, 0, 0, 1.5, 
24.5, 8.4, 7, 12.5, 0, 0, 0, 8.5, 1, 2.5, 14, 12.5, 1, 11.2, 
60, 4.5, 1.9, 0, 11.9, 3.5, 2.4, 6, 24.5, 25, 0, 0, 0, 5, 0, 
4.5, 0, 8, 5.5, 15, 23, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18, 
0, 0, 0, 4.2, 24, 0), Diepoldsau.Hohenems. = c(0.4, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3.5, 4.7, 0, 3.8, 
0, 0, 1.7, 0.8, 0, 0, 0, 0, 12.2, 1.6, 19.9, 1.1, 0.3, 0, 0, 
0, 0, 0, 0, 0, 0.9, 2.1, 0, 2.3, 1.3, 8.2, 8.8, 0, 3.1, 12.7, 
4.2, 0, 0, 13.2, 2.1, 7.4, 0.8, 1.7, 2.2, 0, 0, 0, 0, 0, 0, 3.1, 
6.2, 0.6, 0, 0, 7.2, 1.2, 0, 0, 0, 0, 0, 20.8, 5.5, 0, 0, 5.1, 
10.5, 0, 0, 0, 0, 0, 0, 0, 0, 1.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0.2, 3.7, 0, 0.9, 1.8, 0, 0, 0, 3.2, 0, 2.7, 29.5, 0.6, 0, 
1.4, 6.3, 4.2, 1.7, 6.8, 1.5, 0, 0, 0, 0, 0, 27, 1.8, 0, 0, 0, 
0, 0, 2.3, 0.8, 0, 2.3, 5.5, 4.6, 2.7, 3.3, 0.2, 0, 14.8, 0.9, 
15.5, 3.6, 0.4, 2.1, 0, 1.3, 2.3, 7.5, 47.5, 0, 7.1, 31.2, 7.2, 
8.3, 5.2, 0, 24.2, 0, 2.1, 3.4, 26.4, 0, 0, 6.2, 0, 8.6, 7.5, 
21.3, 0, 1.9, 4.2, 25.3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 4.2, 
1.3, 0, 0, 0.8, 10.2, 21.3, 4.2), Lustenau.Gaissau. = c(0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.8, 4.2, 1.8, 0, 
2.1, 0, 0, 0.8, 3.5, 2, 0, 0, 0, 12.5, 2.4, 20.7, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0.5, 0.8, 0, 2.4, 2.3, 2, 5, 1.5, 3.4, 12.1, 2.3, 
0, 0, 13.7, 1.4, 6.9, 0, 0.3, 0.5, 0, 0, 0, 0, 0, 1, 4.9, 0.3, 
0.2, 0, 0, 3.5, 1.9, 0, 0, 0, 0, 0, 11.5, 0.4, 0, 6.8, 1.9, 9.6, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.3, 0, 0, 0, 5.8, 0, 0, 0, 0, 0, 
1, 8.2, 0, 1.3, 0, 0, 0, 0, 3.2, 0, 1.6, 27.2, 0, 0, 2.9, 11.1, 
1.8, 0.7, 3, 0, 0, 0, 0, 0, 0, 13.1, 0.7, 0, 0, 3.8, 0, 0, 0, 
0, 0, 3.9, 0.5, 6.8, 2.3, 0, 2.3, 2.6, 4.5, 0, 16, 4.9, 0, 0, 
0.2, 0.4, 1.5, 17.2, 43.1, 0, 5.6, 20.8, 4.5, 0, 0, 0.2, 25.6, 
0.3, 1.8, 11.5, 9.4, 0, 0, 0, 0, 5, 7.1, 22.2, 0, 3.8, 7, 18.7, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 30.2, 4.3, 0, 0, 3.3, 6.8, 20.5, 
3.2, 7.8), Engelhartszell.Pfarrkirchen. = c(2.1, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0.2, 0, 0, 0, 0.4, 0.2, 0, 0, 0.4, 
0, 0, 1.4, 0.6, 1.4, 0, 0, 0, 12.5, 1.6, 11.8, 0, 0, 0, 0, 2.3, 
0, 0, 0, 0, 3.2, 8.4, 0, 0, 1.3, 0.4, 1.2, 0, 0, 4.2, 13.5, 12.6, 
21.3, 7.9, 16.8, 21.6, 2.4, 0.7, 8.6, 2.9, 0, 8.3, 12.4, 0, 6.5, 
11.3, 8.7, 0, 0.5, 0, 0, 1.2, 0, 0, 0, 0, 0, 7.8, 0, 0, 0, 6.8, 
0.3, 0.8, 1.3, 0.8, 0, 0, 1.2, 0, 0, 3.2, 0, 0, 0, 0, 0.6, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 18.3, 14.2, 8.6, 11.2, 0, 
0, 0, 0, 3.8, 8.4, 0, 0, 0, 0, 0, 0, 3, 0, 0, 0, 0, 0, 0, 0, 
0, 1.7, 0, 0, 0, 0, 0, 0, 0, 0, 6.1, 2.4, 8.2, 11.6, 7, 0, 0, 
0.9, 0, 81.3, 0, 27.3, 11.8, 4.9, 10.1, 8.7, 6.3, 0, 8.5, 0, 
0.6, 5.2, 18.8, 7.2, 0, 1.1, 0, 0, 0, 4.2, 8.6, 7.7, 0.9, 13.4, 
4, 0, 0, 0, 1.2, 0, 0, 0, 0, 0, 0, 0, 10.3, 0, 0, 2.1, 12.8, 
0, 0), Month = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 7L, 7L, 7L, 7L, 7L, 7L, 
7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L)), row.names = c(NA, 
200L), class = "data.frame")

I think you shared p.data after having made Month field; thats fine, just pointing out that my code uses that rather than making its own. You can continue this way:

library(tidyverse)
library(lubridate)
(data_with_group_col <- tibble(p.data) |>  mutate(       
                                 tempgroup = case_when(Month %in% c(1:4,11:12) ~ "cold",
                                    TRUE ~ "warm")))

Just a hint for further work. A handy way to supply some sample data is the dput() function. In the case of a large dataset something like dput(head(mydata, 100)) should supply the data we need.

Thank you for your help!
I have managed.

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