根據另一個數據幀R中的值填充數據幀中的缺失值

Question

給定兩個數據df1和df2 ，每個數據框有 4 列，我想執行以下操作：

1. 展開df1使其日期范圍介於1948-2016之間。 例如：

seq_df <- data_frame(Date = seq.Date(as.Date("1948-01-01"), 
                                     as.Date("2016-12-31"), 
                                     by="day"))

展開的行應該NA填充的列

2. 將df1中的所有NAs替換為df2中相應的特定於單元格的值。

我嘗試了以下但沒有用：

seq_df <- data_frame(Date = seq.Date(as.Date("1948-01-01"), 
                                     as.Date("2016-12-31"), 
                                     by="day"))


data1=full_join(df1, seq_df) %>% arrange(Date)

樣本數據

df1=structure(list(Date = structure(c(3804, 3805, 3806, 3807, 3808, 
3809, 3810, 3811, 3812, 3813, 3814, 3815, 3816, 3817, 3818, 3819, 
3820, 3821, 3822, 3823, 3824, 3825, 3826, 3827, 3828, 3829, 3830, 
3831, 3832, 3833), class = "Date"), Pr = 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_
), Tmax = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, 13.5, 13, 12, 11.2, 8.5, 12, 13, 17.5, 17.1, 
17.1, 9.5, 6.5, NA), Tmin = c(NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 10.5, 11, 12, 12.5, 7, 
10, 11.5, 7, 5, 4.5, 1, 2)), row.names = c(NA, 30L), class = "data. Frame")

df2=structure(list(Date = structure(c(3804, 3805, 3806, 3807, 3808, 
3809, 3810, 3811, 3812, 3813, 3814, 3815, 3816, 3817, 3818, 3819, 
3820, 3821, 3822, 3823, 3824, 3825, 3826, 3827, 3828, 3829, 3830, 
3831, 3832, 3833), class = "Date"), Pr = 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, 
1.985656032, 0, 0), Tmax = c(16.7579, 16.425, 16.8751, 15.9877, 
15.3752, 15.4138, 15.6038, 14.194, 15.9599, 17.0566, 13.6396, 
15.8548, 15.9682, 17.4073, 17.9238, 10.1966, 10.7029, 13.6226, 
12.7758, 15.0315000000001, 14.5553, 10.0413, 12.5804, 11.7263, 
13.9642, 20.8888, 19.1779, 6.32770000000005, 8.32380000000001, 
10.3664), Tmin = c(2.38980000000004, 3.73170000000005, 2.37440000000004, 
0.744400000000041, 1.34430000000003, 0.914200000000051, -0.107699999999966, 
-0.11099999999999, 1.29250000000002, 2.44490000000002, -0.0418999999999983, 
2.48950000000002, 2.7414, 2.8424, 0.513500000000022, -5.2158, 
-9.0718, 0.44380000000001, -1.51529999999997, -2.18459999999999, 
2.36690000000004, 0.0375000000000227, -3.572, -2.93179999999995, 
-2.54819999999995, 0.20700000000005, 5.50260000000003, 1.28820000000002, 
-2.12149999999997, -7.39839999999998)), row.names = 11841:11870, class = "data. Frame")

Answer 1

我認為您想使用df1存在的所有數據，在缺少df1的地方填寫df2 ，然后填寫其余時間跨度的Date 。

第一步是用df2中的數據填充df1 ，在需要的地方合並（填充NA ），然后刪除重復的列。

full_join(df1, df2, by = "Date", suffix = c("", ".y")) %>%
  mutate(across(c(Pr, Tmax, Tmin), ~ coalesce(., cur_data()[[ paste0(cur_column(), ".y") ]]))) %>%
  select(-ends_with(".y"))
#          Date       Pr    Tmax    Tmin
# 1  1980-06-01 0.000000 16.7579  2.3898
# 2  1980-06-02 0.000000 16.4250  3.7317
# 3  1980-06-03 0.000000 16.8751  2.3744
# 4  1980-06-04 0.000000 15.9877  0.7444
# 5  1980-06-05 0.000000 15.3752  1.3443
# 6  1980-06-06 0.000000 15.4138  0.9142
# 7  1980-06-07 0.000000 15.6038 -0.1077
# 8  1980-06-08 0.000000 14.1940 -0.1110
# 9  1980-06-09 0.000000 15.9599  1.2925
# 10 1980-06-10 0.000000 17.0566  2.4449
# 11 1980-06-11 0.000000 13.6396 -0.0419
# 12 1980-06-12 0.000000 15.8548  2.4895
# 13 1980-06-13 0.000000 15.9682  2.7414
# 14 1980-06-14 0.000000 17.4073  2.8424
# 15 1980-06-15 0.000000 17.9238  0.5135
# 16 1980-06-16 0.000000 10.1966 -5.2158
# 17 1980-06-17 0.000000 10.7029 -9.0718
# 18 1980-06-18 0.000000 13.5000  0.4438
# 19 1980-06-19 0.000000 13.0000 10.5000
# 20 1980-06-20 0.000000 12.0000 11.0000
# 21 1980-06-21 0.000000 11.2000 12.0000
# 22 1980-06-22 0.000000  8.5000 12.5000
# 23 1980-06-23 0.000000 12.0000  7.0000
# 24 1980-06-24 0.000000 13.0000 10.0000
# 25 1980-06-25 0.000000 17.5000 11.5000
# 26 1980-06-26 0.000000 17.1000  7.0000
# 27 1980-06-27 0.000000 17.1000  5.0000
# 28 1980-06-28 1.985656  9.5000  4.5000
# 29 1980-06-29 0.000000  6.5000  1.0000
# 30 1980-06-30 0.000000 10.3664  2.0000

從這里開始，填寫時間跨度只是另一個連接：

result <- full_join(df1, df2, by = "Date", suffix = c("", ".y")) %>%
  mutate(across(c(Pr, Tmax, Tmin), ~ coalesce(., cur_data()[[ paste0(cur_column(), ".y") ]]))) %>%
  select(-ends_with(".y")) %>%
  full_join(seq_df, by = "Date")

（可選擇添加%>% arrange(Date) ）。

--

數據（具有正確的class= ）：

df1 <- structure(list(Date = structure(c(3804, 3805, 3806, 3807, 3808, 3809, 3810, 3811, 3812, 3813, 3814, 3815, 3816, 3817, 3818, 3819, 3820, 3821, 3822, 3823, 3824, 3825, 3826, 3827, 3828, 3829, 3830, 3831, 3832, 3833), class = "Date"), Pr = 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_), Tmax = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 13.5, 13, 12, 11.2, 8.5, 12, 13, 17.5, 17.1, 17.1, 9.5, 6.5, NA), Tmin = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 10.5, 11, 12, 12.5, 7, 10, 11.5, 7, 5, 4.5, 1, 2)), row.names = c(NA, 30L), class = "data.frame")
df2 <- structure(list(Date = structure(c(3804, 3805, 3806, 3807, 3808, 3809, 3810, 3811, 3812, 3813, 3814, 3815, 3816, 3817, 3818, 3819, 3820, 3821, 3822, 3823, 3824, 3825, 3826, 3827, 3828, 3829, 3830, 3831, 3832, 3833), class = "Date"), Pr = 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, 1.985656032, 0, 0), Tmax = c(16.7579, 16.425, 16.8751, 15.9877, 15.3752, 15.4138, 15.6038, 14.194, 15.9599, 17.0566, 13.6396, 15.8548, 15.9682, 17.4073, 17.9238, 10.1966, 10.7029, 13.6226,  12.7758, 15.0315000000001, 14.5553, 10.0413, 12.5804, 11.7263, 13.9642, 20.8888, 19.1779, 6.32770000000005, 8.32380000000001, 10.3664), Tmin = c(2.38980000000004, 3.73170000000005, 2.37440000000004, 0.744400000000041, 1.34430000000003, 0.914200000000051, -0.107699999999966, -0.11099999999999, 1.29250000000002, 2.44490000000002, -0.0418999999999983, 2.48950000000002, 2.7414, 2.8424, 0.513500000000022, -5.2158, -9.0718, 0.44380000000001, -1.51529999999997, -2.18459999999999, 2.36690000000004, 0.0375000000000227,  -3.572, -2.93179999999995, -2.54819999999995, 0.20700000000005, 5.50260000000003, 1.28820000000002, -2.12149999999997, -7.39839999999998)), row.names = 11841:11870, class = "data.frame")
# data_frame is deprecated, use tibble
seq_df <- tibble(Date = seq.Date(as.Date("1948-01-01"), as.Date("2016-12-31"), by="day"))