Question

我有一个表格，其日期为数字，每个日期都有一个值。现在我想添加另一列weekSum，其中包含上周的值总和。但是缺少一些日期（所以我不能总是使用当前和最后6行）。我的表看起来像这样：

df <- data.frame('date' = c(20160309, 20160310, 20160311, 20160312, 20160313, 20160314, 20160315, 20160317, 20160318, 20160319, 20160321), 'value' = c(1, 2, 3, 4, 5, 6, 7 ,8, 9, 10, 11))

date        value
20160309     1
20160310     2
20160311     3
20160312     4
20160313     5
20160314     6
20160315     7
20160316     8     
20160318     9     #17th skipped
20160319    10     
20160321    11     #20th skipped

我想得到以下输出：

date        value    weekSum
20160309     1       NA
20160310     2       NA
20160311     3       NA
20160312     4       NA
20160313     5       NA
20160314     6       NA
20160315     7       28    # 1+2+3+4+5+6+7
20160316     8       35    # 2+3+4+5+6+7+8
20160318     9       39    # 4+5+6+7+8+9
20160319    10       45    # 5+6+7+8+9+10
20160321    11       45    # 7+8+9+10+11

如何做到这一点？

Answer 1

使用基数R可以这样做：

res <- merge(df, data.frame(date = seq(df$date[1], to = df$date[length(d)], by = "days")), all.y = TRUE)

res$weekSum <- NA
for(i in seq_along(res$sum)[-seq_len(6)]){
    res$weekSum[i] <- sum(res$value[(i - 6):i], na.rm = TRUE)
}
res <- res[!is.na(res$value), ]
res
#         date value sum weekSum
#1  2016-03-09     1  NA      NA
#2  2016-03-10     2  NA      NA
#3  2016-03-11     3  NA      NA
#4  2016-03-12     4  NA      NA
#5  2016-03-13     5  NA      NA
#6  2016-03-14     6  NA      NA
#7  2016-03-15     7  28      28
#9  2016-03-17     8  33      35
#10 2016-03-18     9  39      42
#11 2016-03-19    10  45      49
#13 2016-03-21    11  45      56

Answer 2

以下是使用tidyverse工具的方法。此方法使用tidyr::complete构造完整的日期序列，以便按照建议轻松获取当前行和前6行。如果有，请小心 NA中的value值开头，因为目前这些行将在结尾处被过滤掉。如有必要，可以调整以避免这种情况。

library(tidyverse)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following object is masked from 'package:base':
#> 
#>     date
df <- data.frame('date' = c(20160309, 20160310, 20160311, 20160312, 20160313, 20160314, 20160315, 20160317, 20160318, 20160319, 20160321), 'value' = c(1, 2, 3, 4, 5, 6, 7 ,8, 9, 10, 11))
df %>%
  mutate(date = ymd(date)) %>%
  complete(date = seq.Date(min(date), max(date), by = 1)) %>%
  arrange(date) %>%
  mutate(
    newval = replace_na(value, 0),
    weekSum = newval + lag(newval) + lag(newval, 2) + lag(newval, 3) +
      lag(newval, 4) + lag(newval, 5) + lag(newval, 6)
  ) %>%
  select(-newval) %>%
  filter(!is.na(value))
#> # A tibble: 11 x 3
#>    date       value weekSum
#>    <date>     <dbl>   <dbl>
#>  1 2016-03-09    1.     NA 
#>  2 2016-03-10    2.     NA 
#>  3 2016-03-11    3.     NA 
#>  4 2016-03-12    4.     NA 
#>  5 2016-03-13    5.     NA 
#>  6 2016-03-14    6.     NA 
#>  7 2016-03-15    7.     28.
#>  8 2016-03-17    8.     33.
#>  9 2016-03-18    9.     39.
#> 10 2016-03-19   10.     45.
#> 11 2016-03-21   11.     45.

由reprex package（v0.2.0）创建于2018-05-07。

使用取决于日期的值向表中添加列

2 个答案: