R help - May 2022 - Filtering an Entire Dataset based on Several Conditions

Dear friends,

I have a dataframe which every single (i,j) entry (i standing for ith row,
j for jth column) has been normalized (converted to z-scores).

Now I want to filter or subset the dataframe so that I only end up with a a
dataframe containing only entries greater than -3 or less than 3.

How could I accomplish this?

Best,
Paul

	[[alternative HTML version deleted]]

Hi Paul,
Not completely clear what you are looking for.
Please create a 3 x 3 example data frame with dummy data and show what you
want the result to be.



On Mon, May 9, 2022 at 11:24 AM Paul Bernal <paulbernal07 at gmail.com>
wrote:
> Dear friends,
>
> I have a dataframe which every single (i,j) entry (i standing for ith row,
> j for jth column) has been normalized (converted to z-scores).
>
> Now I want to filter or subset the dataframe so that I only end up with a a
> dataframe containing only entries greater than -3 or less than 3.
>
> How could I accomplish this?
>
> Best,
> Paul
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>
	[[alternative HTML version deleted]]

Hi Paul,
Based on my guess that all values have been normalized, I would say:

mat<-(matrix(runif(16,-5,5),4))
df<-as.data.frame(mat)
df[abs(df) < 3]<-NA
df
       V1       V2       V3        V4
1       NA 4.675699 3.166625        NA
2       NA       NA       NA  3.463660
3 4.288831       NA 4.032902 -4.343869
4       NA       NA       NA        NA

Beware that this behavior of data frames may not persist in the
future. You may have to convert to a matrix and then convert the
result back again.

Jim

On Mon, May 9, 2022 at 6:24 PM Paul Bernal <paulbernal07 at gmail.com>
wrote:
>
> Dear friends,
>
> I have a dataframe which every single (i,j) entry (i standing for ith row,
> j for jth column) has been normalized (converted to z-scores).
>
> Now I want to filter or subset the dataframe so that I only end up with a a
> dataframe containing only entries greater than -3 or less than 3.
>
> How could I accomplish this?
>
> Best,
> Paul
>
>         [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.

Hello,

Something like this?
First normalize the data.
Then a apply loop creates a logical matrix giving which numbers are in 
the range -3 to 3.
If they are all TRUE then their sum by rows is equal to the number of 
columns. This creates a logical index i.
Use that index i to subset the scaled data set.

# test data set, remove the Species column (not numeric)
df1 <- iris[-5]

df1_norm <- scale(df1)
i <- rowSums(apply(df1_norm, 2, \(x) x > -3 & x < 3)) ==
ncol(df1_norm)

# returns a matrix
df1_norm[i, ]

# returns a data.frame
as.data.frame(df1_norm[i,])


Hope this helps,

Rui Barradas

?s 09:23 de 09/05/2022, Paul Bernal escreveu:
> Dear friends,
> 
> I have a dataframe which every single (i,j) entry (i standing for ith row,
> j for jth column) has been normalized (converted to z-scores).
> 
> Now I want to filter or subset the dataframe so that I only end up with a a
> dataframe containing only entries greater than -3 or less than 3.
> 
> How could I accomplish this?
> 
> Best,
> Paul
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.