如何将 1 个数据框中的值分配给另一个数据框中的新列

Question

我有2个数据框...

第一个数据帧， mapoc_temp看起来像这样

   month year       ave
1   Jan 2016    6.529222
2   Jan 2017    5.720514
3   Jan 2018    5.786351
4   Feb 2016    6.435445
5   Feb 2017    5.817282
6   Feb 2018    5.790529
7   Mar 2016    6.505259
8   Mar 2017    5.852279
9   Mar 2018    5.683220
10  Apr 2016    6.525603
11  Apr 2017    5.769720
12  Apr 2018    5.762235
13  May 2016    6.425552
14  May 2017    5.855167
15  May 2018    5.778975
16  June    2016    6.488962
17  June    2017    5.871033
18  June    2018    5.720514

mapoc_temp = structure(list(month = structure(c(1L, 1L, 1L, 2L, 2L, 2L), .Label = c("Jan", 
"Feb", "Mar", "Apr", "May", "June", "Jul", "Aug", "Sept", "Oct", 
"Nov", "Dec"), class = "factor"), year = c(2016, 2017, 2018, 
2016, 2017, 2018), ave = c(6.52922242976571, 5.72051368352674, 
5.78635119450037, 6.43544457584707, 5.81728212255571, 5.79052889374
)), row.names = c(NA, -6L), class = c("grouped_df", "tbl_df", 
"tbl", "data.frame"), groups = structure(list(month = structure(1:2, .Label = c("Jan", 
"Feb", "Mar", "Apr", "May", "June", "Jul", "Aug", "Sept", "Oct", 
"Nov", "Dec"), class = "factor"), .rows = list(1:3, 4:6)), row.names = c(NA, 
-2L), class = c("tbl_df", "tbl", "data.frame"), .drop = TRUE))

我的第二个数据框individual_dets看起来像这样

individual_dets = structure(list(location = c("ARB-04", "BIRCHY HEAD", "Boca1", 
"BON-AR-S2", "BON-AR-S2", "BON-W-S5"), month = structure(c(12L, 
10L, 10L, 8L, 11L, 2L), .Label = c("Jan", "Feb", "Mar", "Apr", 
"May", "Jun", "Jul", "Aug", "Sep", "Oct", "Nov", "Dec"), class = c("ordered", 
"factor")), year = c(2018, 2018, 2018, 2018, 2018, 2018), detection_count = c(3L, 
256L, 2L, 4L, 2L, 2L), num_unique_tags = c(1L, 1L, 1L, 1L, 1L, 
1L), total_res_time_in_seconds = c(0, 1182040, 0, 2732221, 0, 
0), latitude = c(24.94808, 44.5713, 26.32559, -49.27732, -49.27732, 
-49.27985), longitude = c(-80.45412, -64.03512, -80.07108, 69.48038, 
69.48038, 69.47853), zone = structure(c(4L, 4L, 4L, 4L, 4L, 4L
), .Label = c("1", "2", "3", "4"), class = "factor"), ave_temp = c(5.740993, 
5.855167, 5.855167, 5.852279, 5.871033, 5.790529)), class = c("grouped_df", 
"tbl_df", "tbl", "data.frame"), row.names = c(NA, -6L), groups = structure(list(
    month = structure(c(2L, 8L, 10L, 11L, 12L), .Label = c("Jan", 
    "Feb", "Mar", "Apr", "May", "Jun", "Jul", "Aug", "Sep", "Oct", 
    "Nov", "Dec"), class = c("ordered", "factor")), .rows = list(
        6L, 4L, 2:3, 5L, 1L)), row.names = c(NA, -5L), class = c("tbl_df", 
"tbl", "data.frame"), .drop = TRUE))

我想从mapoc_dets数据mapoc_dets ave列中获取值，并确保将这些值分配给individual_dets的相应月份和年份

我尝试使用以下代码，但我希望有人可能知道如何缩短此代码

individual_dets = individual_dets %>% 
  group_by(month) %>%
  mutate(ave_temp = 
           if_else(month == "Jan" && year == 2016 , 6.529222,
            if_else (month == "Feb" && year == 2016, 6.435445,
            if_else(month == "Mar" && year == 2016, 6.505259,
            if_else(month == "Apr" && year == 2016, 6.525603,
             if_else (month == "May" && year == 2016, 6.425552,
             if_else (month == "Jun" && year == 2016, 6.488962,
             if_else (month == "Jul" && year == 2016, 6.490498,
             if_else (month == "Aug" && year == 2016, 6.417815,
             if_else (month == "Sep" && year == 2016, 6.492893,
             if_else (month == "Oct" && year == 2016, 6.502256,
             if_else (month == "Nov" && year == 2016, 6.427294,
             if_else (month == "Dec" && year == 2016, 6.508574,

            if_else(month == "Jan" && year == 2017 , 5.720514,
            if_else (month == "Feb" && year == 2017, 5.817282,
            if_else(month == "Mar" && year == 2017, 5.852279,
            if_else(month == "Apr" && year == 2017, 5.769720,
            if_else (month == "May" && year == 2017, 5.855167,
            if_else (month == "Jun" && year == 2017, 5.871033,
            if_else (month == "Jul" && year == 2017, 5.740993,
            if_else (month == "Aug" && year == 2017, 5.786351,
            if_else (month == "Sep" && year == 2017, 5.790529,
            if_else (month == "Oct" && year == 2017, 5.683220,
            if_else (month == "Nov" && year == 2017, 5.762235,
            if_else (month == "Dec" && year == 2017, 5.778975, 

             if_else(month == "Jan" && year == 2018 , 5.786351,
             if_else (month == "Feb" && year == 2018, 5.790529,
             if_else(month == "Mar" && year == 2018, 5.683220,
             if_else(month == "Apr" && year == 2018, 5.762235,
             if_else (month == "May" && year == 2018, 5.778975,
             if_else (month == "Jun" && year == 2018, 5.720514,
             if_else (month == "Jul" && year == 2018, 5.817282,
             if_else (month == "Aug" && year == 2018, 5.852279,
             if_else (month == "Sep" && year == 2018, 5.769720,
             if_else (month == "Oct" && year == 2018, 5.855167,
             if_else (month == "Nov" && year == 2018, 5.871033,
             if_else (month == "Dec" && year == 2018, 5.740993, 0
              ))))))))))))
            )))))))))))))
             ))))))))))))

Answer 1

在ungroup数据集并将要加入的列转换为同一class我们可以使用left_join

library(dplyr)
out <- individual_dets %>% 
         ungroup %>%
         mutate(month = as.character(month)) %>%
         left_join(mapoc_temp %>%
           ungroup %>%
           mutate(month = as.character(month)), by = c("year", "month") )