Select three months of a time series with R

Question

I have a daily data set with temperature data and want to extract seasonal mean values. From daily data it is easy to subset and extract i.e. winter (December to February) values with

my.data.winter<-subset(my.data, format.Date(fecha, "%m")=="12" | format.Date(fecha, "%m")=="01" | format.Date(fecha, "%m")=="02")

giving

dput(my.data.winter)
structure(list(X = c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 20L, 21L, 22L, 23L,
24L, 25L, 26L, 27L, 28L, 29L, 30L, 31L, 32L, 33L, 34L, 35L, 36L,
37L, 38L, 39L, 40L, 41L, 42L, 43L, 44L, 45L, 46L, 47L, 48L, 49L,
50L, 51L, 52L, 53L, 54L, 55L, 56L, 57L, 58L, 59L, 335L, 336L,
337L, 338L, 339L, 340L, 341L, 342L, 343L, 344L, 345L, 346L, 347L,
348L, 349L, 350L, 351L, 352L, 353L, 354L, 355L, 356L, 357L, 358L,
359L, 360L, 361L, 362L, 363L, 364L, 365L, 366L, 367L, 368L, 369L,
370L, 371L, 372L, 373L, 374L, 375L, 376L, 377L, 378L, 379L, 380L,
381L, 382L, 383L, 384L, 385L, 386L, 387L, 388L, 389L, 390L, 391L,
392L, 393L, 394L, 395L, 396L, 397L, 398L, 399L, 400L, 401L, 402L,
403L, 404L, 405L, 406L, 407L, 408L, 409L, 410L, 411L, 412L, 413L,
414L, 415L, 416L, 417L, 418L, 419L, 420L, 421L, 422L, 423L, 424L,
700L, 701L, 702L, 703L, 704L, 705L, 706L, 707L, 708L, 709L, 710L,
711L, 712L, 713L, 714L, 715L, 716L, 717L, 718L, 719L, 720L, 721L,
722L, 723L, 724L, 725L, 726L, 727L, 728L, 729L, 730L, 731L, 732L,
733L, 734L, 735L, 736L, 737L, 738L, 739L, 740L, 741L, 742L, 743L,
744L, 745L, 746L, 747L, 748L, 749L, 750L, 751L, 752L, 753L, 754L,
755L, 756L, 757L, 758L, 759L, 760L, 761L, 762L, 763L, 764L, 765L,
766L, 767L, 768L, 769L, 770L, 771L, 772L, 773L, 774L, 775L, 776L,
777L, 778L, 779L, 780L, 781L, 782L, 783L, 784L, 785L, 786L, 787L,
788L, 789L, 790L, 1066L, 1067L, 1068L, 1069L, 1070L, 1071L, 1072L,
1073L, 1074L, 1075L), fecha = structure(1:250, .Label = c("1982-01-01",
"1982-01-02", "1982-01-03", "1982-01-04", "1982-01-05", "1982-01-06",
"1982-01-07", "1982-01-08", "1982-01-09", "1982-01-10", "1982-01-11",
"1982-01-12", "1982-01-13", "1982-01-14", "1982-01-15", "1982-01-16",
"1982-01-17", "1982-01-18", "1982-01-19", "1982-01-20", "1982-01-21",
"1982-01-22", "1982-01-23", "1982-01-24", "1982-01-25", "1982-01-26",
"1982-01-27", "1982-01-28", "1982-01-29", "1982-01-30", "1982-01-31",
"1982-02-01", "1982-02-02", "1982-02-03", "1982-02-04", "1982-02-05",
"1982-02-06", "1982-02-07", "1982-02-08", "1982-02-09", "1982-02-10",
"1982-02-11", "1982-02-12", "1982-02-13", "1982-02-14", "1982-02-15",
"1982-02-16", "1982-02-17", "1982-02-18", "1982-02-19", "1982-02-20",
"1982-02-21", "1982-02-22", "1982-02-23", "1982-02-24", "1982-02-25",
"1982-02-26", "1982-02-27", "1982-02-28", "1982-12-01", "1982-12-02",
"1982-12-03", "1982-12-04", "1982-12-05", "1982-12-06", "1982-12-07",
"1982-12-08", "1982-12-09", "1982-12-10", "1982-12-11", "1982-12-12",
"1982-12-13", "1982-12-14", "1982-12-15", "1982-12-16", "1982-12-17",
"1982-12-18", "1982-12-19", "1982-12-20", "1982-12-21", "1982-12-22",
"1982-12-23", "1982-12-24", "1982-12-25", "1982-12-26", "1982-12-27",
"1982-12-28", "1982-12-29", "1982-12-30", "1982-12-31", "1983-01-01",
"1983-01-02", "1983-01-03", "1983-01-04", "1983-01-05", "1983-01-06",
"1983-01-07", "1983-01-08", "1983-01-09", "1983-01-10", "1983-01-11",
"1983-01-12", "1983-01-13", "1983-01-14", "1983-01-15", "1983-01-16",
"1983-01-17", "1983-01-18", "1983-01-19", "1983-01-20", "1983-01-21",
"1983-01-22", "1983-01-23", "1983-01-24", "1983-01-25", "1983-01-26",
"1983-01-27", "1983-01-28", "1983-01-29", "1983-01-30", "1983-01-31",
"1983-02-01", "1983-02-02", "1983-02-03", "1983-02-04", "1983-02-05",
"1983-02-06", "1983-02-07", "1983-02-08", "1983-02-09", "1983-02-10",
"1983-02-11", "1983-02-12", "1983-02-13", "1983-02-14", "1983-02-15",
"1983-02-16", "1983-02-17", "1983-02-18", "1983-02-19", "1983-02-20",
"1983-02-21", "1983-02-22", "1983-02-23", "1983-02-24", "1983-02-25",
"1983-02-26", "1983-02-27", "1983-02-28", "1983-12-01", "1983-12-02",
"1983-12-03", "1983-12-04", "1983-12-05", "1983-12-06", "1983-12-07",
"1983-12-08", "1983-12-09", "1983-12-10", "1983-12-11", "1983-12-12",
"1983-12-13", "1983-12-14", "1983-12-15", "1983-12-16", "1983-12-17",
"1983-12-18", "1983-12-19", "1983-12-20", "1983-12-21", "1983-12-22",
"1983-12-23", "1983-12-24", "1983-12-25", "1983-12-26", "1983-12-27",
"1983-12-28", "1983-12-29", "1983-12-30", "1983-12-31", "1984-01-01",
"1984-01-02", "1984-01-03", "1984-01-04", "1984-01-05", "1984-01-06",
"1984-01-07", "1984-01-08", "1984-01-09", "1984-01-10", "1984-01-11",
"1984-01-12", "1984-01-13", "1984-01-14", "1984-01-15", "1984-01-16",
"1984-01-17", "1984-01-18", "1984-01-19", "1984-01-20", "1984-01-21",
"1984-01-22", "1984-01-23", "1984-01-24", "1984-01-25", "1984-01-26",
"1984-01-27", "1984-01-28", "1984-01-29", "1984-01-30", "1984-01-31",
"1984-02-01", "1984-02-02", "1984-02-03", "1984-02-04", "1984-02-05",
"1984-02-06", "1984-02-07", "1984-02-08", "1984-02-09", "1984-02-10",
"1984-02-11", "1984-02-12", "1984-02-13", "1984-02-14", "1984-02-15",
"1984-02-16", "1984-02-17", "1984-02-18", "1984-02-19", "1984-02-20",
"1984-02-21", "1984-02-22", "1984-02-23", "1984-02-24", "1984-02-25",
"1984-02-26", "1984-02-27", "1984-02-28", "1984-02-29", "1984-12-01",
"1984-12-02", "1984-12-03", "1984-12-04", "1984-12-05", "1984-12-06",
"1984-12-07", "1984-12-08", "1984-12-09", "1984-12-10"), class = "factor"),
    V1 = c(290.919993499294, 291.69999348186, 292.149993471801,
    291.859993478283, 291.969993475825, 292.339993467554, 292.289993468672,
    292.179993471131, 291.909993477166, 291.879993477836, 291.819993479177,
    292.74999345839, 292.679993459955, 291.909993477166, 291.489993486553,
    291.479993486777, 291.619993483648, 291.829993478954, 291.959993476048,
    291.229993492365, 291.049993496388, 290.949993498623, 290.949993498623,
    290.939993498847, 290.609993506223, 290.359993511811, 290.369993511587,
    290.369993511587, 290.729993503541, 290.459993509576, 290.409993510693,
    290.549993507564, 290.609993506223, 290.599993506446, 290.459993509576,
    290.459993509576, 290.149993516505, 290.129993516952, 290.149993516505,
    290.38999351114, 290.41999351047, 290.069993518293, 289.919993521646,
    290.009993519634, 289.999993519858, 289.759993525222, 289.799993524328,
    289.779993524775, 289.399993533269, 289.839993523434, 290.039993518963,
    289.669993527234, 289.149993538857, 290.139993516728, 289.999993519858,
    289.889993522316, 289.829993523657, 289.47999353148, 288.999993542209,
    293.28999344632, 293.359993444756, 293.209993448108, 293.099993450567,
    293.039993451908, 292.57999346219, 292.599993461743, 292.719993459061,
    292.799993457273, 292.839993456379, 292.739993458614, 292.769993457943,
    292.839993456379, 292.549993462861, 292.549993462861, 292.439993465319,
    292.159993471578, 290.979993497953, 291.889993477613, 291.369993489236,
    291.249993491918, 291.229993492365, 291.079993495718, 290.799993501976,
    289.949993520975, 290.029993519187, 290.899993499741, 291.199993493035,
    290.849993500859, 290.869993500412, 290.859993500635, 290.269993513823,
    290.209993515164, 290.399993510917, 290.519993508235, 290.569993507117,
    290.649993505329, 290.629993505776, 290.58999350667, 290.689993504435,
    290.75999350287, 290.769993502647, 290.769993502647, 290.609993506223,
    290.469993509352, 290.379993511364, 290.409993510693, 290.7899935022,
    290.359993511811, 289.399993533269, 289.349993534386, 289.539993530139,
    289.50999353081, 289.469993531704, 289.439993532375, 289.47999353148,
    289.47999353148, 289.519993530586, 289.409993533045, 289.219993537292,
    289.189993537962, 289.159993538633, 289.169993538409, 289.719993526116,
    289.659993527457, 289.629993528128, 289.579993529245, 289.289993535727,
    288.999993542209, 289.209993537515, 289.369993533939, 289.449993532151,
    289.449993532151, 289.049993541092, 288.929993543774, 289.13999353908,
    289.319993535057, 289.469993531704, 289.549993529916, 289.589993529022,
    289.629993528128, 289.529993530363, 289.469993531704, 289.389993533492,
    289.409993533045, 289.33999353461, 289.369993533939, 289.379993533716,
    289.589993529022, 289.579993529245, 294.749993413687, 294.289993423969,
    294.149993427098, 294.099993428215, 294.019993430004, 293.949993431568,
    293.849993433803, 293.779993435368, 293.739993436262, 293.629993438721,
    292.699993459508, 292.729993458837, 292.979993453249, 292.769993457943,
    292.549993462861, 292.469993464649, 292.509993463755, 292.559993462637,
    293.099993450567, 293.189993448555, 293.209993448108, 291.999993475154,
    291.849993478507, 291.799993479624, 291.989993475378, 292.269993469119,
    291.389993488789, 291.429993487895, 291.439993487671, 291.2999934908,
    291.339993489906, 291.109993495047, 291.059993496165, 291.039993496612,
    291.009993497282, 290.899993499741, 291.029993496835, 291.149993494153,
    291.179993493482, 291.269993491471, 291.359993489459, 291.339993489906,
    290.38999351114, 290.169993516058, 290.139993516728, 290.169993516058,
    290.309993512928, 290.699993504211, 290.519993508235, 290.509993508458,
    290.459993509576, 290.479993509129, 290.489993508905, 290.319993512705,
    290.24999351427, 290.189993515611, 290.189993515611, 290.229993514717,
    290.209993515164, 290.41999351047, 290.469993509352, 290.099993517622,
    289.389993533492, 290.029993519187, 290.299993513152, 290.329993512481,
    290.299993513152, 290.059993518516, 290.029993519187, 289.819993523881,
    288.729993548244, 288.819993546233, 289.109993539751, 289.109993539751,
    289.129993539304, 289.279993535951, 289.149993538857, 288.76999354735,
    288.899993544444, 289.059993540868, 289.099993539974, 289.129993539304,
    289.13999353908, 289.619993528351, 289.559993529692, 289.33999353461,
    288.999993542209, 288.519993552938, 288.449993554503, 288.419993555173,
    288.239993559197, 294.509993419051, 294.539993418381, 294.319993423298,
    293.279993446544, 293.259993446991, 293.179993448779, 293.099993450567,
    293.029993452132, 292.969993453473, 293.579993439838)), .Names = c("X",
"fecha", "V1"), class = "data.frame", row.names = c(NA, -250L
))

Now I would like to get the mean value for winter season for every distinct year in the series. A first attempt could be

DATE1<-"1982-12-01"
DATE2<-"1983-02-28"
my.newdata<-subset(my.data.winter, my.data.winter$fecha >  DATE1 &  my.data.winter$fecha <  DATE2 )

To use this solution I need to build a date vector or data frame containing pairs of values for DATE1/DATE2 but I would prefer to set just the start value and select three months on. There has to be a cleaner/smarter way. Have checked lubridate (when getting month number from December 1982 and adding 2 months I get "14" when I would like to get February 1983) and dplyr but I can't figure out how this can be done.

Thanks in advance for your help

if you are working with date format. then you can set Date2=Date+3*30 and then use the subset. — Chirayu Chamoli

tbradley tbradley · Accepted Answer · 2017-03-21T15:43:06

Or you can use dplyr:

library(dplyr)
x <- my.data.winter %>%

  #add month and year column using lubridate package
  mutate(month = lubridate::month(fecha), year = lubridate::year(fecha))%>%

  #add the seasons for each value
  mutate(season = case_when(.$month == 12 | .$month == 1 | .$month == 2 ~ "winter",
                            .$month == 3 | .$month == 4 | .$month == 5 ~ "spring",
                            .$month == 6 | .$month == 7 | .$month == 8 ~ "summer",
                            .$month == 9 | .$month == 10 | .$month == 11 ~ "fall")) %>%

  #if month is december, classify it as the next year (for aggregation)
  mutate(year2 = ifelse(.$month == 12, year+1, year)) %>%
  group_by(season, year2) %>%
  summarize(mean = mean(V1))

which gives you :

> x
Source: local data frame [4 x 3]
Groups: season [?]

  season year2       mean
   <chr> <dbl>      <dbl>
1 winter  1982   290.7605
2 winter  1983   290.5127
3 winter  1984   290.9434
4 winter  1985   293.5770

NOTE: you can use this on your entire data set and it will do all of the subsetting for you rather than having to create four separate subsets of your primary data frame

Select three months of a time series with R

1 Answers