在 r 中重叠两年时按月过滤

Question

我正在努力寻找解决方案。

我有以下网格样本数据集（我粘贴了数据集的不同部分）

First one: structure(list(gid = c("117765", "117765", "117765", "117765", 
    "117765", "117765", "117765", "117765", "117765", "117765", "117765", 
    "117765", "117765", "117765", "117765", "117765", "117765", "117765", 
    "117765", "117765", "117765", "117765", "117765", "117765"), 
        country = c("Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
        "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)"
        ), Time = structure(c(3667, 3697, 3727, 3758, 3788, 3819, 
        3849, 3880, 3911, 3941, 3972, 4002, 4033, 4063, 4092, 4123, 
        4153, 4184, 4214, 4245, 4276, 4306, 4337, 4367), class = "Date"), 
        Month = c("01", "02", "03", "04", "05", "06", "07", "08", 
        "09", "10", "11", "12", "01", "02", "03", "04", "05", "06", 
        "07", "08", "09", "10", "11", "12"), SPEI1 = c(-0.702853560447693, 
        2.77506303787231, -1.38380765914917, -0.474617034196854, 
        0.610002398490906, -0.389719426631927, 2.31887650489807, 
        1.47994863986969, 1.66277933120728, 0.399970233440399, -1.47139978408813, 
        -0.435711354017258, -0.510784149169922, -1.15937781333923, 
        0.523077189922333, -0.161062479019165, -0.481528997421265, 
        -1.71726500988007, -1.77663195133209, 0.765306115150452, 
        -0.774405002593994, -0.197176232933998, -1.47615599632263, 
        -0.388415157794952), growstart = c(10, 10, 10, 10, 10, 10, 
        10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 
        10, 10, 10), growend = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
        1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), maincrop = c(28, 
        28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 
        28, 28, 28, 28, 28, 28, 28, 28)), row.names = 572161:572184, class = "data.frame")

_

Second one = structure(list(gid = c("100468", "100468", "100468", "100468", 
"100468", "100468", "100468", "100468", "100468", "100468", "100468", 
"100468", "100468", "100468", "100468", "100468", "100468", "100468", 
"100468", "100468", "100468", "100468", "100468", "100468"), 
    country = c("Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
    "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
    "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
    "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
    "Namibia"), Time = structure(c(3667, 3697, 3727, 3758, 3788, 
    3819, 3849, 3880, 3911, 3941, 3972, 4002, 4033, 4063, 4092, 
    4123, 4153, 4184, 4214, 4245, 4276, 4306, 4337, 4367), class = "Date"), 
    SPEI1 = c(-1.95947802066803, 0.557283878326416, 1.77989518642426, 
    -1.2029390335083, -0.119278997182846, 1.44610369205475, -1.4578732252121, 
    -1.14002466201782, 1.1647777557373, -1.34318947792053, -0.500527501106262, 
    1.50793671607971, -1.45792877674103, -2.00679230690002, -1.51340460777283, 
    -1.9636687040329, -1.40127754211426, -0.182968750596046, 
    0.295145452022552, 0.630711793899536, -0.166128441691399, 
    -0.55840003490448, -2.62139987945557, -1.74482023715973), 
    growstart = c(12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
    12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12), growend = c(4, 
    4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 
    4, 4, 4, 4), maincrop = c(52, 52, 52, 52, 52, 52, 52, 52, 
    52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 
    52), Month = c("01", "02", "03", "04", "05", "06", "07", 
    "08", "09", "10", "11", "12", "01", "02", "03", "04", "05", 
    "06", "07", "08", "09", "10", "11", "12")), row.names = 385:408, class = "data.frame")

_

Third one: structure(list(gid = c("117770", "117770", "117770", "117770", 
"117770", "117770", "117770", "117770", "117770", "117770", "117770", 
"117770", "117770", "117770", "117770", "117770", "117770", "117770", 
"117770", "117770", "117770", "117770", "117770", "117770"), 
    country = c("Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
    "Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)"
    ), Time = structure(c(3667, 3697, 3727, 3758, 3788, 3819, 
    3849, 3880, 3911, 3941, 3972, 4002, 4033, 4063, 4092, 4123, 
    4153, 4184, 4214, 4245, 4276, 4306, 4337, 4367), class = "Date"), 
    SPEI1 = c(0.649401307106018, 1.423499584198, -2.04273128509521, 
    0.271935135126114, 0.616238355636597, -1.03605198860168, 
    1.6733535528183, 1.78166878223419, 1.87084305286407, 1.10145688056946, 
    -1.23061907291412, -1.64128601551056, -1.00736439228058, 
    -1.91670513153076, 1.09841585159302, 0.464365869760513, 1.01759243011475, 
    -1.08844792842865, -0.508061945438385, -0.196570366621017, 
    -0.805905878543854, 0.117944374680519, -0.862984955310822, 
    -1.63738548755646), growstart = c(5, 5, 5, 5, 5, 5, 5, 5, 
    5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5), growend = c(12, 
    12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
    12, 12, 12, 12, 12, 12, 12, 12), maincrop = c(37, 37, 37, 
    37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 
    37, 37, 37, 37, 37, 37), Month = c("01", "02", "03", "04", 
    "05", "06", "07", "08", "09", "10", "11", "12", "01", "02", 
    "03", "04", "05", "06", "07", "08", "09", "10", "11", "12"
    )), row.names = 574081:574104, class = "data.frame")

我有一列“主要作物”，表示我的单元格中的主要作物（gid）和生长季节月份（growstart 和growend）。

对于每个作物/gid/国家/时间，我需要选择与生长季节相对应的行。

我正在努力解决的问题是一些生长季节月份重叠两年，我不知道如何根据这种情况进行过滤？

第一个样本中的示例（重叠两年）：对于 28 号作物，开始生长月份为 10（上一年的 10 月），结束于 1（下一年的 1 月）。 因此，对于根据 gid/国家/时间的这种作物，我将获得 1980 年的 1980-01-16 行（因为我没有 1979 年的数据）以及 1980-10-16 和 1981 之间的行- 01-16 为 1981 年。

第二个样本中的示例（重叠两年）：对于 52 号作物，开始生长月份为 12（上一年的 12 月），结束于 4（下一年的 4 月）。 因此，对于根据 gid/国家/时间的这种作物，我只会得到 1980 年 1980-01-16 和 1980-04-16 之间的行 + 1980-12-16 和 1981-04-16 之间的行1981 年。

第二个样本中的示例（无重叠）：对于 37 号作物，开始生长月份为 5（当年 5 月），到 12 日（当年 12 月）结束。 我只会得到 1980 年 1980-05-16 和 1980-05-16 之间的行 + 1981 年 1981-05-16 和 1981-12-16 之间的行。

请注意，我有一个包含超过 300 万个观察值和不同类型的作物/生长季节的数据框。 因此有 3 个样本。

我真的很感激一种自动化的方式来获得我想要的东西。

谢谢！！

PS：帮帮手喝 10 杯咖啡可以挽救我的理智。

Answer 1

一种方法是使用dplyr ，它允许您进行分组和过滤。 那么一个重要的方面是季节的定义，这取决于它是否是一个有重叠或没有重叠的季节。 值得注意的是，这种方法隐含地假设生长季节在 gid、国家和主要作物水平上是恒定的。

我认为您的方法的一个问题是变量“Month”存储为字符而不是数字变量，这不允许您正确地对信息进行子集化。

在下面的代码中，我将您的三个数据子集合并到一个data.frame中。

library(dplyr)

df <- rbind(one, two, three)
df$Month <- as.numeric(df$Month)

filtered_df <- df %>%
  group_by(gid, country, maincrop) %>%
  filter(Month %in% unique(ifelse(growend <= growstart,
                                  unique(c(seq(growstart[1], 12), seq(1, growend[1]))),
                                  seq(growstart[1], growend[1])))) %>%
  ungroup()

Answer 2

将所有内容合并为一个tibble 。

library(tidyverse)
library(lubridate)

crops %>% 
  mutate(Month = month(Time)) %>% 
  mutate(Year = year(Time), Overlap = growend - growstart < 0) %>% 
  rowwise() %>% 
  filter(
    (Overlap & !(Month %in% (growend+1):(growstart-1))) |
    (!Overlap & Month %in% growstart:growend)
  ) %>% 
  select(names(crops))
#> # A tibble: 34 × 8
#> # Rowwise: 
#>    gid    country             Time       Month  SPEI1 growstart growend maincrop
#>    <chr>  <chr>               <date>     <dbl>  <dbl>     <dbl>   <dbl>    <dbl>
#>  1 117765 Congo, Democratic … 1980-01-16     1 -0.703        10       1       28
#>  2 117765 Congo, Democratic … 1980-10-16    10  0.400        10       1       28
#>  3 117765 Congo, Democratic … 1980-11-16    11 -1.47         10       1       28
#>  4 117765 Congo, Democratic … 1980-12-16    12 -0.436        10       1       28
#>  5 117765 Congo, Democratic … 1981-01-16     1 -0.511        10       1       28
#>  6 117765 Congo, Democratic … 1981-10-16    10 -0.197        10       1       28
#>  7 117765 Congo, Democratic … 1981-11-16    11 -1.48         10       1       28
#>  8 117765 Congo, Democratic … 1981-12-16    12 -0.388        10       1       28
#>  9 100468 Namibia             1980-01-16     1 -1.96         12       4       52
#> 10 100468 Namibia             1980-02-15     2  0.557        12       4       52
#> # … with 24 more rows

使用的数据：

crops <- structure(list(gid = c("117765", "117765", "117765", "117765", 
"117765", "117765", "117765", "117765", "117765", "117765", "117765", 
"117765", "117765", "117765", "117765", "117765", "117765", "117765", 
"117765", "117765", "117765", "117765", "117765", "117765", "100468", 
"100468", "100468", "100468", "100468", "100468", "100468", "100468", 
"100468", "100468", "100468", "100468", "100468", "100468", "100468", 
"100468", "100468", "100468", "100468", "100468", "100468", "100468", 
"100468", "100468", "117770", "117770", "117770", "117770", "117770", 
"117770", "117770", "117770", "117770", "117770", "117770", "117770", 
"117770", "117770", "117770", "117770", "117770", "117770", "117770", 
"117770", "117770", "117770", "117770", "117770"), country = c("Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Namibia", "Namibia", 
"Namibia", "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
"Namibia", "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
"Namibia", "Namibia", "Namibia", "Namibia", "Namibia", "Namibia", 
"Namibia", "Namibia", "Namibia", "Namibia", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)", "Congo, Democratic Republic of (Zaire)", 
"Congo, Democratic Republic of (Zaire)"), Time = structure(c(3667, 
3697, 3727, 3758, 3788, 3819, 3849, 3880, 3911, 3941, 3972, 4002, 
4033, 4063, 4092, 4123, 4153, 4184, 4214, 4245, 4276, 4306, 4337, 
4367, 3667, 3697, 3727, 3758, 3788, 3819, 3849, 3880, 3911, 3941, 
3972, 4002, 4033, 4063, 4092, 4123, 4153, 4184, 4214, 4245, 4276, 
4306, 4337, 4367, 3667, 3697, 3727, 3758, 3788, 3819, 3849, 3880, 
3911, 3941, 3972, 4002, 4033, 4063, 4092, 4123, 4153, 4184, 4214, 
4245, 4276, 4306, 4337, 4367), class = "Date"), Month = c("01", 
"02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12", 
"01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", 
"12", "01", "02", "03", "04", "05", "06", "07", "08", "09", "10", 
"11", "12", "01", "02", "03", "04", "05", "06", "07", "08", "09", 
"10", "11", "12", "01", "02", "03", "04", "05", "06", "07", "08", 
"09", "10", "11", "12", "01", "02", "03", "04", "05", "06", "07", 
"08", "09", "10", "11", "12"), SPEI1 = c(-0.702853560447693, 
2.77506303787231, -1.38380765914917, -0.474617034196854, 0.610002398490906, 
-0.389719426631927, 2.31887650489807, 1.47994863986969, 1.66277933120728, 
0.399970233440399, -1.47139978408813, -0.435711354017258, -0.510784149169922, 
-1.15937781333923, 0.523077189922333, -0.161062479019165, -0.481528997421265, 
-1.71726500988007, -1.77663195133209, 0.765306115150452, -0.774405002593994, 
-0.197176232933998, -1.47615599632263, -0.388415157794952, -1.95947802066803, 
0.557283878326416, 1.77989518642426, -1.2029390335083, -0.119278997182846, 
1.44610369205475, -1.4578732252121, -1.14002466201782, 1.1647777557373, 
-1.34318947792053, -0.500527501106262, 1.50793671607971, -1.45792877674103, 
-2.00679230690002, -1.51340460777283, -1.9636687040329, -1.40127754211426, 
-0.182968750596046, 0.295145452022552, 0.630711793899536, -0.166128441691399, 
-0.55840003490448, -2.62139987945557, -1.74482023715973, 0.649401307106018, 
1.423499584198, -2.04273128509521, 0.271935135126114, 0.616238355636597, 
-1.03605198860168, 1.6733535528183, 1.78166878223419, 1.87084305286407, 
1.10145688056946, -1.23061907291412, -1.64128601551056, -1.00736439228058, 
-1.91670513153076, 1.09841585159302, 0.464365869760513, 1.01759243011475, 
-1.08844792842865, -0.508061945438385, -0.196570366621017, -0.805905878543854, 
0.117944374680519, -0.862984955310822, -1.63738548755646), growstart = c(10, 
10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 
10, 10, 10, 10, 10, 10, 10, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 5, 
5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
5, 5), growend = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 
4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 12, 12, 12, 12, 12, 12, 
12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 
12, 12), maincrop = c(28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 
28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 52, 52, 
52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 52, 
52, 52, 52, 52, 52, 52, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 
37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37, 37)), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -72L))

Answer 3

一个简单的解决方案可能是在两者之间使用一些检查。

如果您想在整个数据集上使用它，您可以按作物分组。

df |> 
    filter(ifelse(growstart > growend,
                  between(as.numeric(Month), 1, min(growend)) | between(as.numeric(Month), min(growstart), 12),
                  between(as.numeric(Month), 1, min(growend)) & between(as.numeric(Month), min(growstart), 12)))

      gid country       Time      SPEI1 growstart growend maincrop Month
1  100468 Namibia 1980-01-16 -1.9594780        12       4       52    01
2  100468 Namibia 1980-02-15  0.5572839        12       4       52    02
3  100468 Namibia 1980-03-16  1.7798952        12       4       52    03
4  100468 Namibia 1980-04-16 -1.2029390        12       4       52    04
5  100468 Namibia 1980-12-16  1.5079367        12       4       52    12
6  100468 Namibia 1981-01-16 -1.4579288        12       4       52    01
7  100468 Namibia 1981-02-15 -2.0067923        12       4       52    02
8  100468 Namibia 1981-03-16 -1.5134046        12       4       52    03
9  100468 Namibia 1981-04-16 -1.9636687        12       4       52    04
10 100468 Namibia 1981-12-16 -1.7448202        12       4       52    12

在 r 中重叠两年时按月过滤

问题描述

3 个解决方案

解决方案1
0 2022-07-02 12:18:09

解决方案2
0 2022-07-02 12:30:00

解决方案3
0 2022-07-02 13:59:25

在 r 中重叠两年时按月过滤

问题描述

3 个解决方案

解决方案1 0 2022-07-02 12:18:09

解决方案2 0 2022-07-02 12:30:00

解决方案3 0 2022-07-02 13:59:25

解决方案1
0 2022-07-02 12:18:09

解决方案2
0 2022-07-02 12:30:00

解决方案3
0 2022-07-02 13:59:25