根据给定条件和经过时间定义标志状态

时间：2017-10-13 12:22:37

标签： r dplyr data.table

我需要创建一个类似于以下内容的标志：

  • 当条件为TRUE时，标志的值始终为1 

    ID Date        Condition Flag Amount
 1 2015.04.01  False        0      0 
 1 2015.05.01  True         1      0 
 1 2015.06.01  True         1      0

  • 在条件设置为false后的一年内，该标志的值始终为1 

    ID Date        Condition Flag Amount
 1 2015.04.01  False        0      0 
 1 2015.05.01  True         1      0 
 1 2015.06.01  True         1      0 
 1 2015.07.01  False        1      0 
 1 2015.08.01  False        1      0 
 1 2015.09.01  False        1      0 
 1 2015.10.01  False        1      0 
 1 2015.11.01  False        1      0 
 1 2015.12.01  False        1      0 
 1 2016.01.01  False        1      0 
 1 2016.02.01  False        1      0 
 1 2016.03.01  False        1      0 
 1 2016.04.01  False        1      0 
 1 2016.05.01  False        1      0 
 1 2016.06.01  False        1      0 
 1 2016.07.01  False        0      0

  • 如果Amount列的值不为0，则年份重新开始，另一年的标志为1 

    ID Date        Condition Flag Amount
 1 2015.04.01  False        0      0 
 1 2015.05.01  True         1      0 
 1 2015.06.01  True         1      0 
 1 2015.07.01  False        1      0 
 1 2015.08.01  False        1      0 
 1 2015.09.01  False        1      0 
 1 2015.10.01  False        1      0 
 1 2015.11.01  False        1     83 
 1 2015.12.01  False        1      0 
 1 2016.01.01  False        1      0 
 1 2016.02.01  False        1      0 
 1 2016.03.01  False        1      0 
 1 2016.04.01  False        1      0 
 1 2016.05.01  False        1      0 
 1 2016.06.01  False        1      0 
 1 2016.07.01  False        1      0 
 1 2016.08.01  False        1      0 
 1 2016.09.01  False        1      0 
 1 2016.10.01  False        1      0 
 1 2016.11.01  False        1      0 
 1 2016.12.01  False        0      0

其他信息：

  • 数据包含多个ID
  • 条件可以多次从FALSE变为TRUE 在一个ID

要点： 如果金额字段为0且条件为TRUE后一年的条件为FALSE，则该标志只能重置为0

请帮助我完成本专栏。

数据： 

> dput(DT)
structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 
2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 
6L, 6L, 6L, 6L, 6L, 6L), Date = c("2014.02.01", "2014.03.01", 
"2014.04.01", "2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", 
"2014.09.01", "2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", 
"2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", 
"2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2015.11.01", 
"2015.12.01", "2016.01.01", "2016.02.01", "2016.03.01", "2016.04.01", 
"2016.05.01", "2016.06.01", "2016.07.01", "2016.08.01", "2016.09.01", 
"2016.10.01", "2016.11.01", "2016.12.01", "2017.01.01", "2017.02.01", 
"2017.03.01", "2017.04.01", "2017.05.01", "2017.06.01", "2017.07.01", 
"2017.08.01", "2017.09.01", "2017.10.01", "2017.11.01", "2017.12.01", 
"2018.01.01", "2018.02.01", "2018.03.01", "2018.04.01", "2018.05.01", 
"2018.06.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", 
"2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", 
"2015.10.01", "2012.01.01", "2012.02.01", "2012.03.01", "2012.04.01", 
"2012.05.01", "2012.06.01", "2012.07.01", "2012.08.01", "2012.09.01", 
"2012.10.01", "2012.11.01", "2012.12.01", "2013.01.01", "2013.02.01", 
"2013.03.01", "2013.04.01", "2013.05.01", "2013.06.01", "2013.07.01", 
"2013.08.01", "2013.09.01", "2013.10.01", "2013.11.01", "2013.12.01", 
"2014.01.01", "2014.02.01", "2014.03.01", "2014.04.01", "2014.05.01", 
"2014.06.01", "2014.07.01", "2014.08.01", "2014.09.01", "2014.10.01", 
"2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", 
"2015.04.01", "2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", 
"2015.09.01", "2015.10.01", "2015.11.01", "2015.12.01", "2016.01.01", 
"2016.02.01", "2016.03.01", "2016.04.01", "2016.05.01", "2016.06.01", 
"2016.07.01", "2016.08.01", "2016.09.01", "2016.10.01", "2016.11.01", 
"2016.12.01", "2017.01.01", "2017.02.01", "2017.03.01", "2017.04.01", 
"2017.05.01", "2017.06.01", "2017.07.01", "2017.08.01", "2014.11.01", 
"2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", 
"2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", 
"2015.10.01", "2015.11.01", "2015.12.01", "2016.01.01", "2016.02.01", 
"2016.03.01", "2016.04.01", "2016.05.01", "2016.06.01", "2016.07.01", 
"2016.08.01", "2016.09.01", "2016.10.01", "2016.11.01", "2016.12.01", 
"2017.01.01", "2017.02.01", "2017.03.01", "2017.04.01", "2017.05.01", 
"2017.06.01", "2017.07.01", "2017.08.01", "2012.12.01", "2013.01.01", 
"2013.02.01", "2013.03.01", "2013.04.01", "2013.05.01", "2013.06.01", 
"2013.07.01", "2013.08.01", "2013.09.01", "2013.10.01", "2013.11.01", 
"2013.12.01", "2014.01.01", "2014.02.01", "2014.03.01", "2014.04.01", 
"2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", "2014.09.01", 
"2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", 
"2015.03.01", "2015.04.01", "2011.02.01", "2011.03.01", "2011.04.01", 
"2011.05.01", "2011.06.01", "2011.07.01", "2011.08.01", "2011.09.01", 
"2011.10.01", "2011.11.01", "2011.12.01", "2012.01.01", "2012.02.01", 
"2012.03.01", "2012.04.01", "2012.05.01", "2012.06.01", "2012.07.01", 
"2012.08.01", "2012.09.01", "2012.10.01", "2012.11.01", "2012.12.01", 
"2013.01.01", "2013.02.01", "2013.03.01", "2013.04.01", "2013.05.01", 
"2013.06.01", "2013.07.01", "2013.08.01", "2013.09.01", "2013.10.01", 
"2013.11.01", "2013.12.01", "2014.01.01", "2014.02.01", "2014.03.01", 
"2014.04.01", "2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", 
"2014.09.01", "2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", 
"2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", 
"2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2015.11.01", 
"2015.12.01", "2016.01.01", "2016.02.01", "2016.03.01", "2016.04.01", 
"2016.05.01", "2016.06.01", "2016.07.01", "2016.08.01", "2016.09.01", 
"2016.10.01", "2016.11.01", "2016.12.01", "2017.01.01", "2017.02.01", 
"2017.03.01", "2017.04.01", "2017.05.01", "2017.06.01", "2017.07.01"
), Condition = c(FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, 
TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, 
FALSE, FALSE, FALSE, FALSE, FALSE, FALSE), Amount = c(10L, 25L, 
20L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 20L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 35L, 70L, 980L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 20L, 75L, 
30L, 0L, 0L, 0L, 0L, 15L, 0L, 0L, 0L, 0L, 0L, 0L, 90L, 90L, 90L, 
150L, 150L, 15L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 15L, 50L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 15L, 30L, 75L, 0L, 0L, 0L, 0L, 15L, 34L, 93L, 0L, 0L, 0L, 
0L, 20L, 30L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
30L, 0L, 0L, 0L, 0L, 0L, 0L, 120L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L)), .Names = c("ID", "Date", 
"Condition", "Amount"), class = c("data.table", "data.frame"), row.names = c(NA, 
-272L), .internal.selfref = <pointer: 0x00000000026b0788>)

1 个答案:

答案 0 :(得分：0)

可能的（不幸的是有点复杂）解决方案：

# load needed packages
library(zoo)
library(lubridate)
library(data.table)

# line 1: convert 'Date' column to date-format
# line 2: create new column 'datetrue' with only the dates for which the Condition is TRUE
# line 3: fill 'datetrue' forward with 'na.locf'
# line 4: create 'dtetrue2' for the rows where 'datetrue' is not NA and
#         'Amount' is higher than zero
# line 5: fill 'datetrue2' forward with 'na.locf'
# line 6: replace 'datetrue' with maximum of 'datetrue' & 'datetrue2' with 'pmax'
# line 7: create 'flag' and set to 'one' where Date is smaller then
#         or equal to 'datetrue'
# line 8: remove the 'datetrue' & 'datetrue2' columns

DT[, Date := as.IDate(Date, '%Y.%m.%d')
   ][!!Condition, datetrue := Date %m+% lubridate::years(1)
     ][, datetrue := na.locf(datetrue, na.rm = FALSE), by = ID
       ][!is.na(datetrue) & Amount > 0, datetrue2 := Date %m+% lubridate::years(1), by = ID
         ][, datetrue2 := na.locf(datetrue2, na.rm = FALSE), by = ID
           ][, datetrue := pmax(datetrue, datetrue2, na.rm = TRUE), by = ID
             ][, flag := as.integer(Date <= datetrue), by = ID
               ][, c('datetrue','datetrue2') := NULL][]

给出了（显示ID == 3的结果）：

> DT[ID == 3]
    ID       Date Condition Amount flag
 1:  3 2012-01-01     FALSE      0   NA
 2:  3 2012-02-01     FALSE      0   NA
 3:  3 2012-03-01     FALSE      0   NA
 4:  3 2012-04-01     FALSE      0   NA
 5:  3 2012-05-01      TRUE      0    1
 6:  3 2012-06-01      TRUE      0    1
 7:  3 2012-07-01      TRUE      0    1
 8:  3 2012-08-01      TRUE      0    1
 9:  3 2012-09-01     FALSE      0    1
10:  3 2012-10-01     FALSE      0    1
11:  3 2012-11-01     FALSE      0    1
12:  3 2012-12-01     FALSE      0    1
13:  3 2013-01-01     FALSE      0    1
14:  3 2013-02-01     FALSE     20    1
15:  3 2013-03-01     FALSE     75    1
16:  3 2013-04-01     FALSE     30    1
17:  3 2013-05-01     FALSE      0    1
18:  3 2013-06-01     FALSE      0    1
19:  3 2013-07-01     FALSE      0    1
20:  3 2013-08-01     FALSE      0    1
21:  3 2013-09-01     FALSE     15    1
22:  3 2013-10-01     FALSE      0    1
23:  3 2013-11-01     FALSE      0    1
24:  3 2013-12-01     FALSE      0    1
25:  3 2014-01-01     FALSE      0    1
26:  3 2014-02-01     FALSE      0    1
27:  3 2014-03-01     FALSE      0    1
28:  3 2014-04-01     FALSE     90    1
29:  3 2014-05-01      TRUE     90    1
30:  3 2014-06-01      TRUE     90    1
31:  3 2014-07-01      TRUE    150    1
32:  3 2014-08-01     FALSE    150    1
33:  3 2014-09-01     FALSE     15    1
34:  3 2014-10-01     FALSE      0    1
35:  3 2014-11-01     FALSE      0    1
36:  3 2014-12-01     FALSE      0    1
37:  3 2015-01-01     FALSE      0    1
38:  3 2015-02-01     FALSE      0    1
39:  3 2015-03-01     FALSE      0    1
40:  3 2015-04-01      TRUE      0    1
41:  3 2015-05-01      TRUE      0    1
42:  3 2015-06-01      TRUE      0    1
43:  3 2015-07-01     FALSE      0    1
44:  3 2015-08-01     FALSE      0    1
45:  3 2015-09-01     FALSE      0    1
46:  3 2015-10-01     FALSE      0    1
47:  3 2015-11-01     FALSE      0    1
48:  3 2015-12-01     FALSE      0    1
49:  3 2016-01-01     FALSE      0    1
50:  3 2016-02-01     FALSE      0    1
51:  3 2016-03-01     FALSE     15    1
52:  3 2016-04-01     FALSE     50    1
53:  3 2016-05-01     FALSE      0    1
54:  3 2016-06-01     FALSE      0    1
55:  3 2016-07-01     FALSE      0    1
56:  3 2016-08-01     FALSE      0    1
57:  3 2016-09-01     FALSE      0    1
58:  3 2016-10-01     FALSE      0    1
59:  3 2016-11-01     FALSE      0    1
60:  3 2016-12-01     FALSE      0    1
61:  3 2017-01-01     FALSE      0    1
62:  3 2017-02-01     FALSE      0    1
63:  3 2017-03-01     FALSE      0    1
64:  3 2017-04-01     FALSE      0    1
65:  3 2017-05-01     FALSE      0    0
66:  3 2017-06-01     FALSE      0    0
67:  3 2017-07-01     FALSE      0    0
68:  3 2017-08-01     FALSE      0    0

使用过的数据：

DT <- structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, NA, NA, NA),
                     Date = c("2014.02.01", "2014.03.01", "2014.04.01", "2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", "2014.09.01", "2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2015.11.01", "2015.12.01", "2016.01.01", "2016.02.01", "2016.03.01", "2016.04.01", "2016.05.01", "2016.06.01", "2016.07.01", "2016.08.01", "2016.09.01", "2016.10.01", "2016.11.01", "2016.12.01", "2017.01.01", "2017.02.01", "2017.03.01", "2017.04.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2012.01.01", "2012.02.01", "2012.03.01", "2012.04.01", "2012.05.01", "2012.06.01", "2012.07.01", "2012.08.01", "2012.09.01", "2012.10.01", "2012.11.01", "2012.12.01", "2013.01.01", "2013.02.01", "2013.03.01", "2013.04.01", "2013.05.01", "2013.06.01", "2013.07.01", "2013.08.01", "2013.09.01", "2013.10.01", "2013.11.01", "2013.12.01", "2014.01.01", "2014.02.01", "2014.03.01", "2014.04.01", "2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", "2014.09.01", "2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2015.11.01", "2015.12.01", "2016.01.01", "2016.02.01", "2016.03.01", "2016.04.01", "2016.05.01", "2016.06.01", "2016.07.01", "2016.08.01", "2016.09.01", "2016.10.01", "2016.11.01", "2016.12.01", "2017.01.01", "2017.02.01", "2017.03.01", "2017.04.01", "2017.05.01", "2017.06.01", "2017.07.01", "2017.08.01", "2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2015.11.01", "2015.12.01", "2016.01.01", "2016.02.01", "2016.03.01", "2016.04.01", "2016.05.01", "2016.06.01", "2016.07.01", "2016.08.01", "2016.09.01", "2016.10.01", "2016.11.01", "2016.12.01", "2017.01.01", "2017.02.01", "2017.03.01", "2017.04.01", "2017.05.01", "2017.06.01", "2017.07.01", "2017.08.01", "2012.12.01", "2013.01.01", "2013.02.01", "2013.03.01", "2013.04.01", "2013.05.01", "2013.06.01", "2013.07.01", "2013.08.01", "2013.09.01", "2013.10.01", "2013.11.01", "2013.12.01", "2014.01.01", "2014.02.01", "2014.03.01", "2014.04.01", "2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", "2014.09.01", "2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", "2011.02.01", "2011.03.01", "2011.04.01", "2011.05.01", "2011.06.01", "2011.07.01", "2011.08.01", "2011.09.01", "2011.10.01", "2011.11.01", "2011.12.01", "2012.01.01", "2012.02.01", "2012.03.01", "2012.04.01", "2012.05.01", "2012.06.01", "2012.07.01", "2012.08.01", "2012.09.01", "2012.10.01", "2012.11.01", "2012.12.01", "2013.01.01", "2013.02.01", "2013.03.01", "2013.04.01", "2013.05.01", "2013.06.01", "2013.07.01", "2013.08.01", "2013.09.01", "2013.10.01", "2013.11.01", "2013.12.01", "2014.01.01", "2014.02.01", "2014.03.01", "2014.04.01", "2014.05.01", "2014.06.01", "2014.07.01", "2014.08.01", "2014.09.01", "2014.10.01", "2014.11.01", "2014.12.01", "2015.01.01", "2015.02.01", "2015.03.01", "2015.04.01", "2015.05.01", "2015.06.01", "2015.07.01", "2015.08.01", "2015.09.01", "2015.10.01", "2015.11.01", "2015.12.01", "2016.01.01", "2016.02.01", "2016.03.01", "2016.04.01", "2016.05.01", "2016.06.01", "2016.07.01", "2016.08.01", "2016.09.01", "2016.10.01", "2016.11.01", "2016.12.01", "2017.01.01", "2017.02.01", "2017.03.01", "2017.04.01", "2017.05.01", "2017.06.01", "2017.07.01", "", "", ""),
                     Condition = c(FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, TRUE, TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, FALSE, NA, NA, NA),
                     Amount = c(10L, 25L, 20L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 35L, 70L, 980L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 20L, 75L, 30L, 0L, 0L, 0L, 0L, 15L, 0L, 0L, 0L, 0L, 0L, 0L, 90L, 90L, 90L, 150L, 150L, 15L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 15L, 50L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 15L, 30L, 75L, 0L, 0L, 0L, 0L, 15L, 34L, 93L, 0L, 0L, 0L, 0L, 20L, 30L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 30L, 0L, 0L, 0L, 0L, 0L, 0L, 120L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, NA, NA, NA)),
                .Names = c("ID", "Date", "Condition", "Amount"), row.names = c(NA, -261L), class = "data.frame")
setDT(DT)
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