标志间隔在r中重叠的行 [英] Flag rows with interval overlap in r
问题描述
我有一个包含电视收看数据的df帧,我想对重叠收看进行质量检查.假设对于同一天,同一家庭,对于每个人来说,每分钟应只记入一个电台或一个频道.
I have a df frame containing TV viewing data, I would like to run a QC check for overlapping viewing. Let's say for the same day, same household, for each individual, each minute should be credited to one station or channel only.
例如,我想标记第8、9行,因为在唯一的家庭中,个人似乎不可能同时(start_hour_minute)观看两个电视台(62,67).我想知道是否有办法标记这些行? 一种按分钟排序的视图,按个人按日查看.
for example, I would like to flag line 8 , 9 , because it seem impossible an individual in a unique household watched two TV stations (62,67) at the same time (start_hour_minute) . I am wondering is there a way to flag this rows? A sort of min by min view by individual by day.
df <- data.frame(stringsAsFactors=FALSE,
date = c("2018-09-02", "2018-09-02", "2018-09-02", "2018-09-02",
"2018-09-02", "2018-09-02", "2018-09-02", "2018-09-02",
"2018-09-02"),
householdID = c(18101276L, 18101276L, 18102843L, 18102843L, 18102843L,
18102843L, 18104148L, 18104148L, 18104148L),
Station_id = c(74L, 74L, 62L, 74L, 74L, 74L, 62L, 62L, 67L),
IndID = c("aa", "aa", "aa", "aa", "aa", "aa", "aa", "aa", "aa"),
Start = c(111300L, 143400L, 030000L, 034900L, 064400L, 070500L, 060400L,
075100L, 075100L),
End = c(111459L, 143759L, 033059L, 035359L, 064759L, 070559L, 060459L,
81559L, 81559L),
start_hour_minute = c(1113L, 1434L, 0300L, 0349L, 0644L, 0705L, 0604L, 0751L, 0751L),
end_hour_minute = c(1114L, 1437L, 0330L, 0353L, 0647L, 0705L, 0604L, 0815L, 0815L))
推荐答案
lubridate
包具有inteval
类对象和%within%
函数,该函数检查时间戳是否在间隔内.您可以使用它来获取标志.
The lubridate
package has an inteval
class object and the %within%
function that checks if a timestamp is within an interval. You can use this to get flags.
使用您在上方提供的虚拟数据...
Using the dummy data you provided above...
data_out <- df %>%
# Get the hour, minute, and second values as standalone numerics.
mutate(
date = ymd(date),
Start_Hour = floor(Start / 10000),
Start_Minute = floor((Start - Start_Hour*10000) / 100),
Start_Second = (Start - Start_Hour*10000) - Start_Minute*100,
End_Hour = floor(End / 10000),
End_Minute = floor((End - End_Hour*10000) / 100),
End_Second = (End - End_Hour*10000) - End_Minute*100,
# Use the hour, minute, second values to create a start-end timestamp.
Start_TS = ymd_hms(date + hours(Start_Hour) + minutes(Start_Minute) + seconds(Start_Second)),
End_TS = ymd_hms(date + hours(Start_Hour) + minutes(Start_Minute) + seconds(Start_Second)),
# Create an interval object.
Watch_Interval = interval(start = Start_TS, end = End_TS)
) %>%
# Group by the IDs.
group_by(householdID, Station_id) %>%
# Flag where the household's interval overlaps with another time.
mutate(
overlap_flag = case_when(
sum(Start_TS %within% as.list(Watch_Interval)) == 0 ~ 0,
sum(Start_TS %within% as.list(Watch_Interval)) > 0 ~ 1,
TRUE ~ NA_real_
)
) %>%
# dplyr doesn't play nice with interval objects, so we should remove Watch_Interval.
select(-Watch_Interval)
使用data_out %>% filter(overlap_flag == 1)
查看标记的值.
注意:dplyr
和lubridate
软件包并非总是能很好地配合使用,尤其是较旧的版本.您可能需要更新每个软件包的版本.
Note: The dplyr
and lubridate
packages don't always play nice together, especially older versions. You may need to update the package versions for each.
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