为每个参数组合创建未来时间戳

Question

我想知道如何为每个参数组合（BranchId、Hour、weekdays）创建未来的时间戳

BranchId      Hour   weekdays     ActivityDate     Total   
    1          11      3      2018-02-06T00:00:00   18
    1          11      3      2018-02-13T00:00:00   23
    1          12      3      2018-02-06T00:00:00   15
    1          12      3      2018-02-13T00:00:00   13
    1          13      3      2018-02-06T00:00:00   24
    1          13      3      2018-02-13T00:00:00   22

目前我只能为一种组合创建未来的时间戳，如下所示：

BranchId    Hour    weekdays    ActivityDate       Total
    1        11        3     2018-02-06T00:00:00Z   18
    1        11        3     2018-02-13T00:00:00Z   23
    1        11        3     2018-02-20T00:00:00Z   
    1        11        3     2018-02-27T00:00:00Z   
    1        11        3     2018-03-06T00:00:00Z   
    1        11        3     2018-03-13T00:00:00Z   

代码是：

min.date <- min(data$ActivityDate)
max.date <- max(data$ActivityDate)


unique.time <- seq(from = min.date,  to = max.date, by = "week")

forecast.time <- seq(from = max.date, by = observation.freq, length.out = 4 + 1)[-1]
all.time <- c(unique.time, forecast.time)
all.time <- data.frame(BranchId = data$BranchId[1], Hour = data$Hour[1], weekdays = data$weekdays[1],ActivityDate = all.time)

# Join the combination with original data
data <- join(all.time, data, by = c("BranchId","Hour", "weekdays", "ActivityDate"), type = "left")

当我应用此代码时结果出现错误，它不会为每个组合创建未来的时间戳：

BranchId    Hour    weekdays    ActivityDate      Total
   1         11        3    2018-02-06T00:00:00Z    18
   1         11        3    2018-02-13T00:00:00Z    23
   1         12        3    2018-02-20T00:00:00Z    
   1         12        3    2018-02-27T00:00:00Z    
   1         13        3    2018-03-06T00:00:00Z    
   1         13        3    2018-03-13T00:00:00Z    

我需要生成多个函数还是 for 循环来处理它？

Answer 1

在 R 中完整

df%>%group_by(BranchId,Hour,weekdays)%>%complete(ActivityDate = seq.Date(min(ActivityDate), min(ActivityDate)+42, by="week"),fill=list(Total=0))
# A tibble: 21 x 5
# Groups:   BranchId, Hour, weekdays [3]
   BranchId  Hour weekdays ActivityDate Total
      <int> <int>    <int>       <date> <dbl>
 1        1    11        3   2018-02-06    18
 2        1    11        3   2018-02-13    23
 3        1    11        3   2018-02-20     0
 4        1    11        3   2018-02-27     0
 5        1    11        3   2018-03-06     0
 6        1    11        3   2018-03-13     0
 7        1    11        3   2018-03-20     0
 8        1    12        3   2018-02-06    15
 9        1    12        3   2018-02-13    13
10        1    12        3   2018-02-20     0

Answer 2

使用 R，您可以使用以下代码创建具有每周间隔的额外日期。使用包padr 中的函数pad，您可以定义将日期添加到data.frame 的时间间隔。使用 group 选项告诉函数应该使用哪些变量来创建新的时间线或填写缺失的日期。您可以指定开始日期和结束日期，以便采用介于两者之间的所有日期，否则它将是 data.frame 中可用的 min 和 max 日期。

min.date <- min(df$ActivityDate)
max.date <- as.Date("2018-03-13T00:00:00Z")

library(padr)

df <- pad(df, interval = "week" , start_val = min.date, end_val = max.date, group = c("BranchId", "Hour", "weekdays"))

# this step can be skipped if you want to keep NA's instead of 0 
df <- fill_by_value(df, value = 0)
df

   BranchId Hour weekdays ActivityDate Total
1         1   11        3   2018-02-06    18
2         1   11        3   2018-02-13    23
3         1   11        3   2018-02-20     0
4         1   11        3   2018-02-27     0
5         1   11        3   2018-03-06     0
6         1   11        3   2018-03-13     0
7         1   12        3   2018-02-06    15
8         1   12        3   2018-02-13    13
9         1   12        3   2018-02-20     0
10        1   12        3   2018-02-27     0
11        1   12        3   2018-03-06     0
12        1   12        3   2018-03-13     0
13        1   13        3   2018-02-06    24
14        1   13        3   2018-02-13    22
15        1   13        3   2018-02-20     0
16        1   13        3   2018-02-27     0
17        1   13        3   2018-03-06     0
18        1   13        3   2018-03-13     0

数据：

df <- structure(list(BranchId = c(1L, 1L, 1L, 1L, 1L, 1L), 
                     Hour = c(11L, 11L, 12L, 12L, 13L, 13L), 
                     weekdays = c(3L, 3L, 3L, 3L, 3L, 3L),
                     ActivityDate = as.Date(c("2018-02-06T00:00:00", "2018-02-13T00:00:00","2018-02-06T00:00:00", 
                                      "2018-02-13T00:00:00", "2018-02-06T00:00:00", "2018-02-13T00:00:00")), 
                     Total = c(18L, 23L, 15L, 13L, 24L, 22L)), 
                .Names = c("BranchId", "Hour", "weekdays", "ActivityDate", "Total"),
                class = "data.frame", row.names = c(NA, -6L))