有条件地在R中执行difftime
[英]Conditionally Perform difftime in R
问题描述
I have a data table with devices that are inspected "annually." 
我有一个数据表，其中包含“每年”检查的设备。 When the device has an inspection code "AC" (inspection_disposition_cd="AC"), then I need to count the days passed since the inspection record listed in the row directly above it. 当设备的检验代码为“ AC”（inspection_disposition_cd =“ AC”）时，我需要计算自其上方的行中列出的检验记录以来经过的天数。
The code I am using does the math just fine, however, I am struggling with coding so that ONLY the rows that have the AC code receive this action. 我正在使用的代码可以很好地进行数学运算，但是，我正在努力进行编码，以便只有具有AC代码的行才能执行此操作。 Can anyone provide any advice as to how to single out these rows? 谁能提供任何有关如何挑选这些行的建议？
This is the working code: 这是工作代码：
DispNotClear2$First<-c(0,with(DispNotClear2,difftime(insp_dt[2:length(insp_dt)],insp_dt[1], unit="days")))
DispNotClear2$BETWEEN<-c(0,with(DispNotClear2,diff(insp_dt[1:(length(insp_dt)-1)],unit="days")))}
Also, here are 30 rows of sample data from my data table: 另外，这是我的数据表中的30行示例数据：
library(data.table)
SampleData <- setDT(structure(list(record_num = c(12354L, 6764L, 9959L, 94L, 16463L,
6859L, 80678L, 87555L, 77980L, 2839L, 4785L, 6082L, 28271L, 54L,
23000L, 2565L, 3507L, 25607L, 106L, 14621L, 33525L, 6335L, 24970L,
4851L, 77057L, 17247L, 14488L, 2754L, 88945L, 2710L), device_num = c("2P4564",
"1P27589", "1P9215", "1P32077", "3P2093", "1P29651", "3P13054",
"1P14559", "3P7242", "1P30282", "1P12286", "1P13149", "3P10127",
"1P18885", "4P5121", "1P14621", "1P6278", "1P35255", "1P28871",
"3P2643", "3P12113", "1P31196", "4P2597", "1W5192", "2P5643",
"3P6750", "3F1928", "1P11978", "1P33505", "1P14572"), year = c(2016,
2011, 2016, 2010, 2011, 2013, 2014, 2015, 2013, 2012, 2015, 2016,
2013, 2015, 2010, 2011, 2011, 2015, 2013, 2012, 2016, 2011, 2015,
2016, 2012, 2016, 2011, 2015, 2010, 2014), inspection_type_cd = c("CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)", "CATEGORY 1 (1YR)",
"CATEGORY 1 (1YR)"), inspection_disposition_cd = c("AC", "AC",
"AC", "AU", "AC", "AC", "AU", "AC", "AC", "AC", "AC", "AU", "AU",
"AU", "AU", "AU", "RD", "AU", "AU", "AC", "AU", "AC", "AU", "AU",
"AC", "AU", "AU", "AC", "AU", "AC"), remarks = c("2015 AFFIRMATION OF CORRECTION",
NA, "2016 AOC", NA, "PENALTY PAID", "2012 AOC", NA, "2015 AFFIRMATION OF CORRECTION",
"2013 AFFIRMATION OF CORRECTION", "2011 CORRECTION", "2015 AFFIRMATION OF CORRECTION",
NA, NA, "2015 CAT1", NA, NA, "AFFIRMATION OF CORRECTION FILED 68 DAYS LATE",
NA, NA, "2012 CORRECTION", "2016 CAT1", "2010 AFFIRMATION OF CORRECTION",
NA, NA, "2012 CORRECTION", "2016 CAT1", NA, "2015 AFFIRMATION OF CORRECTION",
NA, "2013 AOC"), insp_dt = structure(c(16911, 15271, 17060, 14784,
15014, 16009, 16339, 16658, 16044, 15363, 16576, 17151, 16069,
16444, 14714, 15184, 15237, 16631, 16059, 15415, 16979, 14995,
16748, 17137, 15644, 16973, 15211, 16636, 14957, 16087), class = "Date"),
days_late = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 68, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA)), .Names = c("record_num", "device_num",
"year", "inspection_type_cd", "inspection_disposition_cd", "remarks",
"insp_dt", "days_late"), class = "data.frame", row.names = c(NA, -30L)))
which looks like 看起来像
record_num device_num year inspection_type_cd inspection_disposition_cd remarks insp_dt days_late
1: 12354 2P4564 2016 CATEGORY 1 (1YR) AC 2015 AFFIRMATION OF CORRECTION 2016-04-20 NA
2: 6764 1P27589 2011 CATEGORY 1 (1YR) AC NA 2011-10-24 NA
3: 9959 1P9215 2016 CATEGORY 1 (1YR) AC 2016 AOC 2016-09-16 NA
4: 94 1P32077 2010 CATEGORY 1 (1YR) AU NA 2010-06-24 NA
5: 16463 3P2093 2011 CATEGORY 1 (1YR) AC PENALTY PAID 2011-02-09 NA
6: 6859 1P29651 2013 CATEGORY 1 (1YR) AC 2012 AOC 2013-10-31 NA
7: 80678 3P13054 2014 CATEGORY 1 (1YR) AU NA 2014-09-26 NA
8: 87555 1P14559 2015 CATEGORY 1 (1YR) AC 2015 AFFIRMATION OF CORRECTION 2015-08-11 NA
9: 77980 3P7242 2013 CATEGORY 1 (1YR) AC 2013 AFFIRMATION OF CORRECTION 2013-12-05 NA
10: 2839 1P30282 2012 CATEGORY 1 (1YR) AC 2011 CORRECTION 2012-01-24 NA
11: 4785 1P12286 2015 CATEGORY 1 (1YR) AC 2015 AFFIRMATION OF CORRECTION 2015-05-21 NA
12: 6082 1P13149 2016 CATEGORY 1 (1YR) AU NA 2016-12-16 NA
13: 28271 3P10127 2013 CATEGORY 1 (1YR) AU NA 2013-12-30 NA
14: 54 1P18885 2015 CATEGORY 1 (1YR) AU 2015 CAT1 2015-01-09 NA
15: 23000 4P5121 2010 CATEGORY 1 (1YR) AU NA 2010-04-15 NA
16: 2565 1P14621 2011 CATEGORY 1 (1YR) AU NA 2011-07-29 NA
17: 3507 1P6278 2011 CATEGORY 1 (1YR) RD AFFIRMATION OF CORRECTION FILED 68 DAYS LATE 2011-09-20 68
18: 25607 1P35255 2015 CATEGORY 1 (1YR) AU NA 2015-07-15 NA
19: 106 1P28871 2013 CATEGORY 1 (1YR) AU NA 2013-12-20 NA
20: 14621 3P2643 2012 CATEGORY 1 (1YR) AC 2012 CORRECTION 2012-03-16 NA
21: 33525 3P12113 2016 CATEGORY 1 (1YR) AU 2016 CAT1 2016-06-27 NA
22: 6335 1P31196 2011 CATEGORY 1 (1YR) AC 2010 AFFIRMATION OF CORRECTION 2011-01-21 NA
23: 24970 4P2597 2015 CATEGORY 1 (1YR) AU NA 2015-11-09 NA
24: 4851 1W5192 2016 CATEGORY 1 (1YR) AU NA 2016-12-02 NA
25: 77057 2P5643 2012 CATEGORY 1 (1YR) AC 2012 CORRECTION 2012-10-31 NA
26: 17247 3P6750 2016 CATEGORY 1 (1YR) AU 2016 CAT1 2016-06-21 NA
27: 14488 3F1928 2011 CATEGORY 1 (1YR) AU NA 2011-08-25 NA
28: 2754 1P11978 2015 CATEGORY 1 (1YR) AC 2015 AFFIRMATION OF CORRECTION 2015-07-20 NA
29: 88945 1P33505 2010 CATEGORY 1 (1YR) AU NA 2010-12-14 NA
30: 2710 1P14572 2014 CATEGORY 1 (1YR) AC 2013 AOC 2014-01-17 NA
record_num device_num year inspection_type_cd inspection_disposition_cd remarks insp_dt days_late
2 个解决方案
解决方案1
0 2017-04-02 19:14:17
An alternative solution with dplyr and lubridate : dplyr和lubridate的替代解决方案：
library(lubridate)
library(dplyr)
SampleData %>%
filter(inspection_disposition_cd=="AC") %>%
mutate(day_passed = today()-insp_dt)
解决方案2
0 2017-04-03 11:59:12
If I understood correctly, below code takes difference between above row for the records where inspection_disposition_cd=="AC" 如果我理解正确，则下面的代码将记录的上一行与上一行之间的区别作为其中inspection_disposition_cd=="AC"
SampleData[,day_passed:=ifelse(inspection_disposition_cd=="AC",difftime(shift(insp_dt,1),insp_dt,units = "days"),0)]
alternatively 或者
SampleData[inspection_disposition_cd=="AC",day_passed:=difftime(shift(insp_dt,1),insp_dt,units = "days")]
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