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Chris Beeley

2010-Aug-24 17:19 UTC

[R] How to remove rows based on frequency of factor and then difference date scores

Hello-

A basic question which has nonetheless floored me entirely. I have a
dataset which looks like this:

Type  ID     Date            Value
A       1    16/09/2020       8
A       1     23/09/2010      9
B       3     18/8/2010        7
B       1     13/5/2010        6

There are two Types, which correspond to different individuals in
different conditions, and loads of ID labels (1:50) corresponding to
the different individuals in each condition, and measurements at
different times (from 1 to 10 measurements) for each individual.

I want to perform the following operations:

1) Delete all individuals for whom only one measurement is available.
In the dataset above, you can see that I want to delete the row Type B
ID 3, and Type B ID 1, but without deleting the Type A ID 1 data
because there is more than one measurement for Type A ID 1 (but not
for Type B ID1)

2) Produce difference scores for each of the Dates, so each individual
(Type A ID1 and all the others for whom more than one measurement
exists) starts at Date "1" and goes up in integers according to how
many days have elapsed.

I just know there's some incredibly cunning R-ish way of doing this
but after many hours of fiddling I have had to admit defeat.

I would be very grateful for any words of advice.

Many thanks,
Chris Beeley,
Institute of Mental Health, UK

David Winsemius

2010-Aug-24 17:53 UTC

head link

[R] How to remove rows based on frequency of factor and then difference date scores

On Aug 24, 2010, at 1:19 PM, Chris Beeley wrote:
> Hello-
>
> A basic question which has nonetheless floored me entirely. I have a
> dataset which looks like this:
>
> Type  ID     Date            Value
> A       1    16/09/2020       8
> A       1     23/09/2010      9
> B       3     18/8/2010        7
> B       1     13/5/2010        6
>
> There are two Types, which correspond to different individuals in
> different conditions, and loads of ID labels (1:50) corresponding to
> the different individuals in each condition, and measurements at
> different times (from 1 to 10 measurements) for each individual.
>
> I want to perform the following operations:
>
> 1) Delete all individuals for whom only one measurement is available.
> In the dataset above, you can see that I want to delete the row Type B
> ID 3, and Type B ID 1, but without deleting the Type A ID 1 data
> because there is more than one measurement for Type A ID 1 (but not
> for Type B ID1)
>
> 2) Produce difference scores for each of the Dates, so each individual
> (Type A ID1 and all the others for whom more than one measurement
> exists) starts at Date "1" and goes up in integers according to
how
> many days have elapsed.
>
> I just know there's some incredibly cunning R-ish way of doing this
> but after many hours of fiddling I have had to admit defeat.
Not sure about terribly cunning. Let's assume your dataframe was read  
in with stringsAsFactors=FALSE and is called txt.df:


 > txt.df$dt2 <- as.Date(txt.df$Date, format="%d/%m/%Y")
 > txt.df
   Type ID       Date Value        dt2
1    A  1 16/09/2020     8 2020-09-16
2    A  1 23/09/2010     9 2010-09-23
3    B  3  18/8/2010     7 2010-08-18
4    B  1  13/5/2010     6 2010-05-13

 > txt.df$nn <- ave(txt.df$ID,txt.df$ID, FUN=length)
 > txt.df
   Type ID       Date Value        dt2 nn
1    A  1 16/09/2020     8 2020-09-16  3
2    A  1 23/09/2010     9 2010-09-23  3
3    B  3  18/8/2010     7 2010-08-18  1
4    B  1  13/5/2010     6 2010-05-13  3
 > txt.df[ -which( txt.df$nn <=1), ]
   Type ID       Date Value        dt2 nn
1    A  1 16/09/2020     8 2020-09-16  3
2    A  1 23/09/2010     9 2010-09-23  3
4    B  1  13/5/2010     6 2010-05-13  3

# Task #1 accomplished

 > tapply(txt.df$dt2, txt.df$ID, function(x) x[1] -x)
$`1`
Time differences in days
[1]    0 3646 3779

$`3`
Time difference of 0 days

 > unlist( tapply(txt.df$dt2, txt.df$ID, function(x) x[1] -x) )
   11   12   13    3
    0 3646 3779    0
 > txt.df$diffdays <- unlist( tapply(txt.df$dt2, txt.df$ID,  
function(x) x[1] -x) )
 > txt.df
   Type ID       Date Value        dt2 nn diffdays
1    A  1 16/09/2020     8 2020-09-16  3        0
2    A  1 23/09/2010     9 2010-09-23  3     3646
3    B  3  18/8/2010     7 2010-08-18  1     3779
4    B  1  13/5/2010     6 2010-05-13  3        0
 >


>
> I would be very grateful for any words of advice.
>
> Many thanks,
> Chris Beeley,
> Institute of Mental Health, UK
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
David Winsemius, MD
West Hartford, CT

Abhijit Dasgupta, PhD

2010-Aug-24 17:56 UTC

head link

[R] How to remove rows based on frequency of factor and then difference date scores

An answer to 1)

 > x = data.frame(Type=c('A','A','B','B'),
ID=c(1,1,3,1), Date =
c('16/09/2010','23/09/2010','18/8/2010','13/5/2010'),
Value=c(8,9,7,6))
 > x
   Type ID       Date Value
1    A  1 16/09/2010     8
2    A  1 23/09/2010     9
3    B  3  18/8/2010     7
4    B  1  13/5/2010     6
 > x$Date = as.Date(x$Date,format='%d/%m/%Y')
 > library(plyr)
 > x$uniqueID = paste(x$Type, x$ID, sep='')
 > nobs = daply(x, ~uniqueID, nrow)
 > keep = names(nobs)[nobs>1]
 > newx = x[x$uniqueID %in% keep,]

An answer to 2)
 > require(plyr)
 > ddply(newx, ~uniqueID, transform, newDate = as.numeric(Date - 
min(Date)+1))


On 08/24/2010 01:19 PM, Chris Beeley wrote:> Hello-
>
> A basic question which has nonetheless floored me entirely. I have a
> dataset which looks like this:
>
> Type  ID     Date            Value
> A       1    16/09/2020       8
> A       1     23/09/2010      9
> B       3     18/8/2010        7
> B       1     13/5/2010        6
>
> There are two Types, which correspond to different individuals in
> different conditions, and loads of ID labels (1:50) corresponding to
> the different individuals in each condition, and measurements at
> different times (from 1 to 10 measurements) for each individual.
>
> I want to perform the following operations:
>
> 1) Delete all individuals for whom only one measurement is available.
> In the dataset above, you can see that I want to delete the row Type B
> ID 3, and Type B ID 1, but without deleting the Type A ID 1 data
> because there is more than one measurement for Type A ID 1 (but not
> for Type B ID1)
>
> 2) Produce difference scores for each of the Dates, so each individual
> (Type A ID1 and all the others for whom more than one measurement
> exists) starts at Date "1" and goes up in integers according to
how
> many days have elapsed.
>
> I just know there's some incredibly cunning R-ish way of doing this
> but after many hours of fiddling I have had to admit defeat.
>
> I would be very grateful for any words of advice.
>
> Many thanks,
> Chris Beeley,
> Institute of Mental Health, UK
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>    

-- 

Abhijit Dasgupta, PhD
Director and Principal Statistician
ARAASTAT
Ph: 301.385.3067
E: adasgupta at araastat.com
W: http://www.araastat.com

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