Calculating the probability that the Signature column has the status “Y” in the last 30 days












0












$begingroup$


I am doing this formula in R:



for (i  in 1:ifinal)
{
df$FPRateSignature30d[i] <-
length(
which(
df$status == "Y" &
` df$Signature==df$Signature[i]& df$date>= (as_datetime(df$date[i])duration(30, days')) &` df$date <
as_datetime(df$date[i])
)
) / length(which(
df$Signature == df$Signature[i] &
df$date >= (as_datetime(df$date[i]) - duration(30, 'days')) &
``df$date < as_datetime(df$date[i])
))
}


but I have ~350K of rows in the real data, and takes me a lot doing this with for loops.



Here it is the data sample:



df <- data.frame(c("1","2","3","4","5","6"),c("Attribute1", "Attribute1", "Attribute2", "Attribute2", "Attribute2", "Attribute1"),
c("2018-11-01 00:00:19", "2018-10-25 00:00:54", "2018-11-01 10:03:27",
"2018-11-01 00:01:23", "2018-11-01 00:01:25","2018-10-21 00:00:55"), c("Y","Y","Y","N","Y","N"))
names(df) <- c("ID","Signature", "date", "status")
df$date <- as.POSIXct(df$date)
ifinal<-nrow(df)


Do you know any other way to do it maybe applying a function?










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$endgroup$

















    0












    $begingroup$


    I am doing this formula in R:



    for (i  in 1:ifinal)
    {
    df$FPRateSignature30d[i] <-
    length(
    which(
    df$status == "Y" &
    ` df$Signature==df$Signature[i]& df$date>= (as_datetime(df$date[i])duration(30, days')) &` df$date <
    as_datetime(df$date[i])
    )
    ) / length(which(
    df$Signature == df$Signature[i] &
    df$date >= (as_datetime(df$date[i]) - duration(30, 'days')) &
    ``df$date < as_datetime(df$date[i])
    ))
    }


    but I have ~350K of rows in the real data, and takes me a lot doing this with for loops.



    Here it is the data sample:



    df <- data.frame(c("1","2","3","4","5","6"),c("Attribute1", "Attribute1", "Attribute2", "Attribute2", "Attribute2", "Attribute1"),
    c("2018-11-01 00:00:19", "2018-10-25 00:00:54", "2018-11-01 10:03:27",
    "2018-11-01 00:01:23", "2018-11-01 00:01:25","2018-10-21 00:00:55"), c("Y","Y","Y","N","Y","N"))
    names(df) <- c("ID","Signature", "date", "status")
    df$date <- as.POSIXct(df$date)
    ifinal<-nrow(df)


    Do you know any other way to do it maybe applying a function?










    share|improve this question









    New contributor




    user190888 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















      0












      0








      0





      $begingroup$


      I am doing this formula in R:



      for (i  in 1:ifinal)
      {
      df$FPRateSignature30d[i] <-
      length(
      which(
      df$status == "Y" &
      ` df$Signature==df$Signature[i]& df$date>= (as_datetime(df$date[i])duration(30, days')) &` df$date <
      as_datetime(df$date[i])
      )
      ) / length(which(
      df$Signature == df$Signature[i] &
      df$date >= (as_datetime(df$date[i]) - duration(30, 'days')) &
      ``df$date < as_datetime(df$date[i])
      ))
      }


      but I have ~350K of rows in the real data, and takes me a lot doing this with for loops.



      Here it is the data sample:



      df <- data.frame(c("1","2","3","4","5","6"),c("Attribute1", "Attribute1", "Attribute2", "Attribute2", "Attribute2", "Attribute1"),
      c("2018-11-01 00:00:19", "2018-10-25 00:00:54", "2018-11-01 10:03:27",
      "2018-11-01 00:01:23", "2018-11-01 00:01:25","2018-10-21 00:00:55"), c("Y","Y","Y","N","Y","N"))
      names(df) <- c("ID","Signature", "date", "status")
      df$date <- as.POSIXct(df$date)
      ifinal<-nrow(df)


      Do you know any other way to do it maybe applying a function?










      share|improve this question









      New contributor




      user190888 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I am doing this formula in R:



      for (i  in 1:ifinal)
      {
      df$FPRateSignature30d[i] <-
      length(
      which(
      df$status == "Y" &
      ` df$Signature==df$Signature[i]& df$date>= (as_datetime(df$date[i])duration(30, days')) &` df$date <
      as_datetime(df$date[i])
      )
      ) / length(which(
      df$Signature == df$Signature[i] &
      df$date >= (as_datetime(df$date[i]) - duration(30, 'days')) &
      ``df$date < as_datetime(df$date[i])
      ))
      }


      but I have ~350K of rows in the real data, and takes me a lot doing this with for loops.



      Here it is the data sample:



      df <- data.frame(c("1","2","3","4","5","6"),c("Attribute1", "Attribute1", "Attribute2", "Attribute2", "Attribute2", "Attribute1"),
      c("2018-11-01 00:00:19", "2018-10-25 00:00:54", "2018-11-01 10:03:27",
      "2018-11-01 00:01:23", "2018-11-01 00:01:25","2018-10-21 00:00:55"), c("Y","Y","Y","N","Y","N"))
      names(df) <- c("ID","Signature", "date", "status")
      df$date <- as.POSIXct(df$date)
      ifinal<-nrow(df)


      Do you know any other way to do it maybe applying a function?







      r






      share|improve this question









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      user190888 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      share|improve this question









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      share|improve this question




      share|improve this question








      edited 7 hours ago









      Jamal

      30.3k11116226




      30.3k11116226






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      asked 7 hours ago









      user190888user190888

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