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R 基于条件的列求和

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R 基于条件的列求和,r,tidyverse,R,Tidyverse,我有一个由三列组成的数据框：x、ID和date\u time。 “x”列是一个变量x的记录，ID表示记录的内容，而date\u time表示记录的时间。请参见下面的一段数据帧 从这个数据框中，我想计算一个新的数据框，它有七列：“测量”、“ID”和“日期”、“x_4_10_day”、“day_total”、“x_4_10_night”、“night_total” “测量”。此列应说明给定ID的测量值。测量值从23:00:00开始，然后运行到第二天22:59:59。然而，测量在随机时间开始，因此第一

我有一个由三列组成的数据框：x、ID和date\u time。 “x”列是一个变量x的记录，ID表示记录的内容，而date\u time表示记录的时间。请参见下面的一段数据帧

从这个数据框中，我想计算一个新的数据框，它有七列：“测量”、“ID”和“日期”、“x_4_10_day”、“day_total”、“x_4_10_night”、“night_total”

  • “测量”。此列应说明给定ID的测量值。测量值从23:00:00开始，然后运行到第二天22:59:59。然而，测量在随机时间开始，因此第一次测量的持续时间不是24小时。也不是24小时内的最后一次测量
  • “身份证”。指示给定测量的ID
  • “日期”。此列应以以下格式显示给定测量中最后一次记录的日期：yyyy.mm.dd
  • “x_4_10_日”：测量分为白天（7:00:00-22:59:59）和夜晚（23:00:00-6:59:59）。此列应显示给定测量中每天总时间（以分钟为单位）x在4-10之间（均包括在内）。在4-10之间记录x可以被视为x在4-10之间持续5分钟，因为每次记录之间有5分钟
  • “Day_total”：此列应显示一天中测量的总时间（以分钟为单位）x。x中缺少应减去的值。缺少的x值保留为空。对于每次缺失的测量，应从总时间中减去5分钟。此外，一些测量开始时间晚于7:00
  • “x_4_10_night”：此列应显示给定测量中每晚x在4-10（均包括在内）之间的总时间（分钟）
  • “Night_total”：此列应表明在一个晚上测量的总时间（以分钟为单位）x。x中缺少应减去的值。缺少的x值保留为空。对于每次缺失的测量，应从总时间中减去5分钟
    • 每个独特的测量值都应该有一行。到目前为止，我有一个代码可以正确返回列：“Measurement”、“ID”和“Date”：

    df1$mydate = as.Date(df1$date_time, format = "%Y.%m.%d %H:%M:%S")
df1$tm <- as.numeric(df1$date_time)
df1$dts <- 86400*as.numeric(df1$mydate)
df2 <- df1 %>% 
group_by(ID,mydate) %>% 
transform(date = case_when(((dts-3600)<tm & tm<(dts+82800)) ~paste0(mydate), ((dts+82800)<=tm) ~paste0(mydate+1) )) %>% 
select(ID,date) %>%   
unique() %>% 
group_by(ID) %>% 
mutate(measurement = row_number())
    我已将id=14的
    id
    添加到您的数据帧中，其中仅包含夜间值。这可能是您正在寻找的。请注意，您的预期值并不完全符合您的要求

    df11 <- structure(list(date_time = c("2020.03.02 22:00:17", "2020.03.02 22:05:17", 
                             "2020.03.02 22:10:17", "2020.03.02 22:35:17", "2020.03.02 22:40:17", 
                             "2020.03.02 22:45:17", "2020.03.02 22:50:17", "2020.03.02 22:55:17", 
                             "2020.03.02 23:00:17", "2020.03.02 23:05:17", "2020.03.02 23:10:17", 
                             "2020.03.02 23:15:17", "2020.03.02 23:20:17", "2020.03.02 23:25:17", 
                             "2020.03.02 23:30:17", "2020.03.02 23:35:17", "2020.03.02 23:40:17", 
                             "2020.03.02 23:45:17", "2020.03.02 23:50:17", "2020.03.02 23:55:17", 
                             "2020.03.03 00:00:17", "2020.03.03 00:55:17", "2020.03.03 01:00:17", 
                             "2020.03.03 01:05:17", "2020.03.03 01:10:17", "2020.03.03 01:15:17", 
                             "2020.03.03 01:20:17", "2020.03.03 01:25:17", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.03.02 23:45:17", "2020.03.02 23:50:17", "2020.03.02 23:55:17", 
                             "2020.03.03 00:00:17", "2020.03.03 00:55:17", "2020.03.03 01:00:17" 
                             ), 
                      x = c("7.55", "4.55", "4.55", "12", 
                            "12", "10", "10", "4.3", "", "", "4.3", "4.3", "4.3", "", "4.3", 
                            "12", "12", "12", "2", "12", "12", "", "8", "3", "3", "2", "2", 
                            "", "12", "10", "10", "4.3", "4.3", "4.3", "4.3", "4.3", "4.3", 
                            "4.3", "4.3", "12", "12", "12", "12", "12", "12", "12",
                            "12", "10", "10", "4.3", "4.3", "4.3"),
               id = c(12L, 12L, 
                      12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                      12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                      13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
                      13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L)), 
               row.names = c(NA, 52L), class = "data.frame")

df11$xn <- as.numeric(df11$x)
df1 <- df11 %>% transform(xmin = ifelse((xn<4 | xn>10 | is.na(xn)),0,5 ),
                          xmint = ifelse(is.na(xn),-5,5 ))
df1$dateTime = as_datetime(df1$date_time, format = "%Y.%m.%d %H:%M:%S")
df1$mydate = as.Date(df1$date_time, format = "%Y.%m.%d %H:%M:%S")

df1$tm <- as.numeric(df1$dateTime)
df1$dts <- 86400*as.numeric(df1$mydate)

df2 <- df1 %>% group_by(id,mydate) %>% 
         transform(date = case_when(((dts-3600)<tm & tm<(dts+82800) )~paste0(mydate),((dts+82800)<=tm)~paste0(mydate+1) )) %>%
         transform(dayrnight = ifelse((tm>=(dts+25200) & tm<(dts+82800) ),'day','night' ) ) %>% 
         group_by(id,date,dayrnight) %>% 
         dplyr::summarise(x_4_10 = sum(xmin), total = sum(xmint)) %>% 
         pivot_wider(id_cols = c(id,date), names_from = dayrnight, values_from = c("x_4_10", "total")) %>% 
         mutate_if(is.numeric , replace_na, replace = 0) %>% 
         group_by(id) %>% mutate(measurement = row_number()) %>% 
         select(id,date,measurement,x_4_10_day,total_day,x_4_10_night,total_night)

> df2
# A tibble: 4 x 7
# Groups:   id [3]
     id date       measurement x_4_10_day total_day x_4_10_night total_night
  <int> <chr>            <int>      <dbl>     <dbl>        <dbl>       <dbl>
1    12 2020-03-02           1         30        40            0           0
2    12 2020-03-03           2          0         0           25          50
3    13 2020-05-09           1         50        90            0           0
4    14 2020-03-03           1          0         0           25          30

    df11%
分组依据（id）%>%mutate（measurement=行编号（））%>%
选择（id、日期、测量、x_4_10_日、总日、x_4_10_夜、总夜）
>df2
#一个tibble:4x7
#组别:id[3]
id日期测量x_4_10_天总计x_4_10_夜总计
1    12 2020-03-02           1         30        40            0           0
2    12 2020-03-03           2          0         0           25          50
3    13 2020-05-09           1         50        90            0           0
4    14 2020-03-03           1          0         0           25          30
    我已在数据框中添加了仅包含夜间值的
    id=14
    。这可能是您正在寻找的。请注意，您的预期值并不完全符合您的要求

    df11 <- structure(list(date_time = c("2020.03.02 22:00:17", "2020.03.02 22:05:17", 
                             "2020.03.02 22:10:17", "2020.03.02 22:35:17", "2020.03.02 22:40:17", 
                             "2020.03.02 22:45:17", "2020.03.02 22:50:17", "2020.03.02 22:55:17", 
                             "2020.03.02 23:00:17", "2020.03.02 23:05:17", "2020.03.02 23:10:17", 
                             "2020.03.02 23:15:17", "2020.03.02 23:20:17", "2020.03.02 23:25:17", 
                             "2020.03.02 23:30:17", "2020.03.02 23:35:17", "2020.03.02 23:40:17", 
                             "2020.03.02 23:45:17", "2020.03.02 23:50:17", "2020.03.02 23:55:17", 
                             "2020.03.03 00:00:17", "2020.03.03 00:55:17", "2020.03.03 01:00:17", 
                             "2020.03.03 01:05:17", "2020.03.03 01:10:17", "2020.03.03 01:15:17", 
                             "2020.03.03 01:20:17", "2020.03.03 01:25:17", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.05.09 08:39:32", "2020.05.09 08:39:32", 
                             "2020.03.02 23:45:17", "2020.03.02 23:50:17", "2020.03.02 23:55:17", 
                             "2020.03.03 00:00:17", "2020.03.03 00:55:17", "2020.03.03 01:00:17" 
                             ), 
                      x = c("7.55", "4.55", "4.55", "12", 
                            "12", "10", "10", "4.3", "", "", "4.3", "4.3", "4.3", "", "4.3", 
                            "12", "12", "12", "2", "12", "12", "", "8", "3", "3", "2", "2", 
                            "", "12", "10", "10", "4.3", "4.3", "4.3", "4.3", "4.3", "4.3", 
                            "4.3", "4.3", "12", "12", "12", "12", "12", "12", "12",
                            "12", "10", "10", "4.3", "4.3", "4.3"),
               id = c(12L, 12L, 
                      12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                      12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                      13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
                      13L, 13L, 13L, 13L, 13L, 14L, 14L, 14L, 14L, 14L, 14L)), 
               row.names = c(NA, 52L), class = "data.frame")

df11$xn <- as.numeric(df11$x)
df1 <- df11 %>% transform(xmin = ifelse((xn<4 | xn>10 | is.na(xn)),0,5 ),
                          xmint = ifelse(is.na(xn),-5,5 ))
df1$dateTime = as_datetime(df1$date_time, format = "%Y.%m.%d %H:%M:%S")
df1$mydate = as.Date(df1$date_time, format = "%Y.%m.%d %H:%M:%S")

df1$tm <- as.numeric(df1$dateTime)
df1$dts <- 86400*as.numeric(df1$mydate)

df2 <- df1 %>% group_by(id,mydate) %>% 
         transform(date = case_when(((dts-3600)<tm & tm<(dts+82800) )~paste0(mydate),((dts+82800)<=tm)~paste0(mydate+1) )) %>%
         transform(dayrnight = ifelse((tm>=(dts+25200) & tm<(dts+82800) ),'day','night' ) ) %>% 
         group_by(id,date,dayrnight) %>% 
         dplyr::summarise(x_4_10 = sum(xmin), total = sum(xmint)) %>% 
         pivot_wider(id_cols = c(id,date), names_from = dayrnight, values_from = c("x_4_10", "total")) %>% 
         mutate_if(is.numeric , replace_na, replace = 0) %>% 
         group_by(id) %>% mutate(measurement = row_number()) %>% 
         select(id,date,measurement,x_4_10_day,total_day,x_4_10_night,total_night)

> df2
# A tibble: 4 x 7
# Groups:   id [3]
     id date       measurement x_4_10_day total_day x_4_10_night total_night
  <int> <chr>            <int>      <dbl>     <dbl>        <dbl>       <dbl>
1    12 2020-03-02           1         30        40            0           0
2    12 2020-03-03           2          0         0           25          50
3    13 2020-05-09           1         50        90            0           0
4    14 2020-03-03           1          0         0           25          30

    df11%
分组依据（id）%>%mutate（measurement=行编号（））%>%
选择（id、日期、测量、x_4_10_日、总日、x_4_10_夜、总夜）
>df2
#一个tibble:4x7
#组别:id[3]
id日期测量x_4_10_天总计x_4_10_夜总计
1    12 2020-03-02           1         30        40            0           0
2    12 2020-03-03           2          0         0           25          50
3    13 2020-05-09           1         50        90            0           0
4    14 2020-03-03           1          0         0           25          30
    我花了一些时间，但你可能想要这个

    样本数据（在
    13
    中的日期/时间有点变化）都是相同的

    df <- structure(list(date_time = c("2020.03.02 22:00:17", "2020.03.02 22:05:17", 
                             "2020.03.02 22:10:17", "2020.03.02 22:35:17", "2020.03.02 22:40:17", 
                             "2020.03.02 22:45:17", "2020.03.02 22:50:17", "2020.03.02 22:55:17", 
                             "2020.03.02 23:00:17", "2020.03.02 23:05:17", "2020.03.02 23:10:17", 
                             "2020.03.02 23:15:17", "2020.03.02 23:20:17", "2020.03.02 23:25:17", 
                             "2020.03.02 23:30:17", "2020.03.02 23:35:17", "2020.03.02 23:40:17", 
                             "2020.03.02 23:45:17", "2020.03.02 23:50:17", "2020.03.02 23:55:17", 
                             "2020.03.03 00:00:17", "2020.03.03 00:55:17", "2020.03.03 01:00:17", 
                             "2020.03.03 01:05:17", "2020.03.03 01:10:17", "2020.03.03 01:15:17", 
                             "2020.03.03 01:20:17", "2020.03.03 01:25:17", "2020.05.09 08:39:32", 
                             "2020.05.09 08:44:32", "2020.05.09 08:49:32", "2020.05.09 08:54:32", 
                             "2020.05.09 08:59:32", "2020.05.09 09:39:32", "2020.05.09 09:44:32", 
                             "2020.05.09 09:49:32", "2020.05.09 09:59:32", "2020.05.09 10:39:32", 
                             "2020.05.09 11:39:32", "2020.05.09 12:39:32", "2020.05.09 13:39:32", 
                             "2020.05.09 14:39:32", "2020.05.09 15:39:32", "2020.05.09 16:39:32", 
                             "2020.05.09 17:39:32", "2020.05.09 18:39:32"), id = c(12L, 12L, 
                                                                                   12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                                                                                   12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                                                                                   13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
                                                                                   13L, 13L, 13L, 13L, 13L), x = c("7.55", "4.55", "4.55", "12", 
                                                                                                                   "12", "10", "10", "4.3", "", "", "4.3", "4.3", "4.3", "", "4.3", 
                                                                                                                   "12", "12", "12", "2", "12", "12", "", "8", "3", "3", "2", "2", 
                                                                                                                   "", "12", "10", "10", "4.3", "4.3", "4.3", "4.3", "4.3", "4.3", 
                                                                                                                   "4.3", "4.3", "12", "12", "12", "12", "12", "12", "12")), row.names = c(NA, 
                                                                                                                                                                                           46L), class = "data.frame")

    df%as_-tible（）%>%
变换（x=作为数值（x），
日期时间=作为日期时间（日期时间），
id=as.character（id））%>%
变异（d_n=ifelse（小时（日期时间）>=7和小时（日期时间）=4和x%
mutate（valid_m=ifelse（is.na（valid_m），0，valid_m））%>%#有效度量
安排（id、日期和时间）%>%
分组依据（id）%>%
变异（有效期=数值（提前期（日期时间）-日期时间））%>%
过滤器（！is.na（validm_d））%>%
分组人（id、日期、数字、有效数字）%>%
总结（x_tm=总和（有效值））%>%
解组（）%>%
轴宽（名称从=d\u n，值从=x\u tm，值从=0）%>%
分组人（id，日期）%>%
突变（日=sum（日），夜=sum（夜））%>%
筛选器（有效的\u m！=0）%>%
分组依据（id）%>%
变异（测量=行数（））%>%
选择（id，测量，日期，x_4_10_day=天，x_4_10_total=天，
x_4_10_night=夜间，x_4_10_Total n=夜间）
    期望的结果

    id    measurement Date       x_4_10_day x_4_10_total x_4_10_night x_4_10_totaln
  <chr>       <int> <date>          <dbl>        <dbl>        <dbl>         <dbl>
1 12              1 2020-03-02         50           60           20            60
2 12              2 2020-03-03          0            0            5            85
3 13              1 2020-05-09        235          600            0             0

    id测量日期x_4_10_日x_4_10_总计x_4_10_夜间x_4_10_总计
1 12              1 2020-03-02         50           60           20            60
2 12              2 2020-03-03          0            0            5            85
3 13              1 2020-05-09        235          600            0             0
    在这个解决方案中，我删除了每个测量的最后一个值，因为我不确定该测量要进行多长时间。您可以适当地更改代码。“day”的最后一次测量基本上结束于2300小时，因此第一行的结果应该比显示的结果少17秒。

    我花了一些时间，但可能您想要这个

    样本数据（在
    13
    中的日期/时间有点变化）都是相同的

    df <- structure(list(date_time = c("2020.03.02 22:00:17", "2020.03.02 22:05:17", 
                             "2020.03.02 22:10:17", "2020.03.02 22:35:17", "2020.03.02 22:40:17", 
                             "2020.03.02 22:45:17", "2020.03.02 22:50:17", "2020.03.02 22:55:17", 
                             "2020.03.02 23:00:17", "2020.03.02 23:05:17", "2020.03.02 23:10:17", 
                             "2020.03.02 23:15:17", "2020.03.02 23:20:17", "2020.03.02 23:25:17", 
                             "2020.03.02 23:30:17", "2020.03.02 23:35:17", "2020.03.02 23:40:17", 
                             "2020.03.02 23:45:17", "2020.03.02 23:50:17", "2020.03.02 23:55:17", 
                             "2020.03.03 00:00:17", "2020.03.03 00:55:17", "2020.03.03 01:00:17", 
                             "2020.03.03 01:05:17", "2020.03.03 01:10:17", "2020.03.03 01:15:17", 
                             "2020.03.03 01:20:17", "2020.03.03 01:25:17", "2020.05.09 08:39:32", 
                             "2020.05.09 08:44:32", "2020.05.09 08:49:32", "2020.05.09 08:54:32", 
                             "2020.05.09 08:59:32", "2020.05.09 09:39:32", "2020.05.09 09:44:32", 
                             "2020.05.09 09:49:32", "2020.05.09 09:59:32", "2020.05.09 10:39:32", 
                             "2020.05.09 11:39:32", "2020.05.09 12:39:32", "2020.05.09 13:39:32", 
                             "2020.05.09 14:39:32", "2020.05.09 15:39:32", "2020.05.09 16:39:32", 
                             "2020.05.09 17:39:32", "2020.05.09 18:39:32"), id = c(12L, 12L, 
                                                                                   12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                                                                                   12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 
                                                                                   13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 
                                                                                   13L, 13L, 13L, 13L, 13L), x = c("7.55", "4.55", "4.55", "12", 
                                                                                                                   "12", "10", "10", "4.3", "", "", "4.3", "4.3", "4.3", "", "4.3", 
                                                                                                                   "12", "12", "12", "2", "12", "12", "", "8", "3", "3", "2", "2", 
                                                                                                                   "", "12", "10", "10", "4.3", "4.3", "4.3", "4.3", "4.3", "4.3", 
                                                                                                                   "4.3", "4.3", "12", "12", "12", "12", "12", "12", "12")), row.names = c(NA, 
                                                                                                                                                                                           46L), class = "data.frame")

    df%as_-tible（）%>%
变换（x=作为数值（x），
日期时间=作为日期时间（日期）

    id    measurement Date       x_4_10_day x_4_10_total x_4_10_night x_4_10_totaln
  <chr>       <int> <date>          <dbl>        <dbl>        <dbl>         <dbl>
1 12              1 2020-03-02         50           60           20            60
2 12              2 2020-03-03          0            0            5            85
3 13              1 2020-05-09        235          600            0             0