Question

我正在使用按group_by包dplyr函数分组的数据集。每个组都有自己的时间索引，即假定由12个月的序列组成。这意味着它可以从1月开始到12月结束，或者在其他情况下可以从前一年的6月开始到明年5月结束。

以下是数据集示例：

     ID       DATE
      8 2017-01-31
      8 2017-02-28
      8 2017-03-31
      8 2017-04-30
      8 2017-05-31
      8 2017-06-30
      8 2017-07-31
      8 2017-08-31
      8 2017-09-30
      8 2017-10-31
      8 2017-11-30
      8 2017-12-31
     32 2017-01-31
     32 2017-02-28
     32 2017-03-31
     32 2017-04-30
     32 2017-05-31
     32 2017-06-30
     32 2017-07-31
     32 2017-08-31
     32 2017-09-30
     32 2017-10-31
     32 2017-11-30
     32 2017-12-31
     45 2016-09-30
     45 2016-10-31
     45 2016-11-30
     45 2016-12-31
     45 2017-01-31
     45 2017-02-28
     45 2017-03-31
     45 2017-04-30
     45 2017-05-31
     45 2017-06-30
     45 2017-07-31
     45 2017-08-31

问题在于，如果存在所谓的＆＃34;跳跃＆＃34;，换句话说，如果日期一致，我就无法确认或验证数据集维度。 r中是否有任何简单的方法可以执行此操作，也许是来自tibbletime包的一些修改/组合功能。

任何帮助都将受到赞赏。

提前谢谢。

Answer 1

以下是我通常使用data.table解决此问题的方法 - 来自base的cut.Date()和seq.Date()函数是逻辑的核心，所以你使用相同的如果需要，可以使用dplyr。

library(data.table)

## Convert to data.table
setDT(df)

## Convert DATE to a date in case it wasn't already
df[,DATE := as.Date(DATE)]

## Order by ID and Date
setkey(df,ID,DATE)

## Create a column with the month of each date
df[,Month := as.Date(cut.Date(DATE, breaks = "months"))]

## Generate a sequence of Dates by month for the number of observations
## in each group -- .N
df[,ExpectedMonth := seq.Date(from = min(Month),
                              by = "months",
                              length.out = .N), by = .(ID)]

## Create a summary table to test whether an ID had 12 observations where
## the actual month was equal to the expected month
Test <- df[Month == ExpectedMonth, .(Valid = ifelse(.N == 12L,TRUE,FALSE)), by = .(ID)]

print(Test)
#    ID Valid
# 1:  8  TRUE
# 2: 32  TRUE
# 3: 45  TRUE

## Do a no-copy join of Test to df based on ID
## and create a column in df based on the 'Valid' column in Test
df[Test, Valid := i.Valid, on = "ID"]

## The final output:
head(df)
#    ID       DATE      Month ExpectedMonth Valid
# 1:  8 2017-01-31 2017-01-01    2017-01-01  TRUE
# 2:  8 2017-02-28 2017-02-01    2017-02-01  TRUE
# 3:  8 2017-03-31 2017-03-01    2017-03-01  TRUE
# 4:  8 2017-04-30 2017-04-01    2017-04-01  TRUE
# 5:  8 2017-05-31 2017-05-01    2017-05-01  TRUE
# 6:  8 2017-06-30 2017-06-01    2017-06-01  TRUE

如果你真的想要使用自我加入并跳过创建Test

，你也可以做一些更紧凑的事情

setDT(df)

df[,DATE := as.Date(DATE)]
setkey(df,ID,DATE)
df[,Month := as.Date(cut.Date(DATE, breaks = "months"))]
df[,ExpectedMonth := seq.Date(from = min(Month), by = "months", length.out = .N), keyby = .(ID)]
df[df[Month == ExpectedMonth,.(Valid = ifelse(.N == 12L,TRUE,FALSE)),keyby = .(ID)], Valid := i.Valid]

验证时间序列索引

1 个答案: