[R] Checking for duplicate rows in data frame efficiently
I wrote something to check for duplicate rows in a data frame, but it is too
inefficient. Is there a way to do this without the nested loops?
This code correctly indicates rows 1-7, 1-8, 2-9 and 7-8 are duplicates.
m - matrix(c(1,1,1,1,1, 2,2,2,2,2, 6,6,6,6,6, 3,3,3,3,3, 4,4,4,4,4,
5,5,5,5,5, 1,1,1,1,1, 1,1,1,1,1, 2,2,2,2,2, 7,7,7,7,7), ncol=5, byrow=TRUE)
df - data.frame(m)
df
X1 X2 X3 X4 X5
1 1 1 1 1 1
2 2 2 2 2 2
3 6 6 6 6 6
4 3 3 3 3 3
5 4 4 4 4 4
6 5 5 5 5 5
7 1 1 1 1 1
8 1 1 1 1 1
9 2 2 2 2 2
10 7 7 7 7 7
compareTwoRows - function(row1, row2){
+ numCol - 5
+ logicalRow - row1==row2
+ duplicate - sum(logicalRow)==numCol
+ return(as.numeric(duplicate))}
same - matrix(0, byrow=TRUE, ncol=10,nrow=10)
for (j in 1:9)
+ for (k in (j+1):10)
+ same[j,k] - compareTwoRows(df[j,],df[k,])
same
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,]000000110 0
[2,]000000001 0
[3,]000000000 0
[4,]000000000 0
[5,]000000000 0
[6,]000000000 0
[7,]000000010 0
[8,]000000000 0
[9,]000000000 0
[10,]000000000 0
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[R] shifted window of string
basically I need to create a sliding window in a string. a way to explain this
is:
v -
c(a,b,c,d,e,f,g,h,i,j,k,l,m,n,o,p,q,r,s,t,u,v,w,x,y)
window - 5
shift - 2
I want a matrix of characters with window columns filled with v by filling
a row, then shifting over shift and continuing to the next row until v is
exhausted. You can assume v will evenly fit m
so the result needs to look like this matrix where each row is shifted 2 (in
this case):
m
[,1] [,2] [,3] [,4] [,5]
[1,] a b c d e
[2,] c d e f g
[3,] e f g h i
[4,] g h i j k
[5,] i j k l m
[6,] k l m n o
[7,] m n o p q
[8,] o p q r s
[9,] q r s t u
[10,] s t u v w
[11,] t u v w x
This needs to be very efficient as my data is large, loops would be too slow.
Any ideas? It could also be done in a string and then put into the matrix but
I don't think this would be easier.
I will want to put this in a function:
shiftedMatrix - function(v, window=5, shift=2){...
return(m)}
thanks
dhs
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[R] color2D.matplot not giving colors
I am using color2D.matplot to plot a matrix about 400 by 200. The values in the matrix are 0:5 and NA. The resulting plot is not color, but shaded b/w. I tried to figure out how to add colors, I would like something like c(blue, green, red, cyan, green) #example motifx - matrix(NA, nrow=100,ncol=20) motifx[,1:5] - 1 motifx[,6:10] - 2 motifx[,11:15] - 3 motifx[,15:19] - 4 motifx color2D.matplot(motifx, na.color=white,show.legend=TRUE) or is there a better function to use than color2D.matplot? [[alternative HTML version deleted]] __ R-help@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.
[R] aggregate by factor
I have a data frame with two columns, a factor and a numeric. I want to create data frame with the factor, its frequency and the median of the numeric column head(motifList) events score 1 aeijm -0.2500 2 begjm -0.2500 3 afgjm -0.2500 4 afhjm -0.2500 5 aeijm -0.2500 6 aehjm 0.0833 To get the frequency table of events: motifTable - as.data.frame(table(motifList$events)) head(motifTable) Var1 Freq 1 aeijm 110 2 begjm 46 3 afgjm 337 4 afhjm 102 5 aehjm 190 6 adijm 18 Now get the score column back in. motifTable2 - merge(motifList, motifTable, by=events) head(motifTable2) events percent freq 1 adgjm 0. 111 2 adgjm NA 111 3 adgjm 0.1333 111 4 adgjm 0.0667 111 5 adgjm -0.1667 111 6 adgjm NA 111 Then lastly to aggregate on the events column getting the median of the score motifTable3 - aggregate.data.frame(motifTable2, by=list(motifTable2$events), FUN=median, na.rm=TRUE) Error in median.default(X[[1L]], ...) : need numeric data Which gives the error as events are a factor. Can someone enlighten me to a more obvious approach? dhs [[alternative HTML version deleted]] __ R-help@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.
Re: [R] aggregate by factor
On 30 Jan 2010, at 4:20 PM, David Winsemius wrote:
On Jan 30, 2010, at 4:09 PM, david hilton shanabrook wrote:
I have a data frame with two columns, a factor and a numeric. I want to
create data frame with the factor, its frequency and the median of the
numeric column
head(motifList)
events score
1 aeijm -0.2500
2 begjm -0.2500
3 afgjm -0.2500
4 afhjm -0.2500
5 aeijm -0.2500
6 aehjm 0.0833
To get the frequency table of events:
motifTable - as.data.frame(table(motifList$events))
head(motifTable)
Var1 Freq
1 aeijm 110
2 begjm 46
3 afgjm 337
4 afhjm 102
5 aehjm 190
6 adijm 18
Now get the score column back in.
motifTable2 - merge(motifList, motifTable, by=events)
head(motifTable2)
events percent freq
1 adgjm 0. 111
2 adgjm NA 111
3 adgjm 0.1333 111
4 adgjm 0.0667 111
5 adgjm -0.1667 111
6 adgjm NA 111
Then lastly to aggregate on the events column getting the median of the score
motifTable3 - aggregate.data.frame(motifTable2,
by=list(motifTable2$events), FUN=median, na.rm=TRUE)
Error in median.default(X[[1L]], ...) : need numeric data
Which gives the error as events are a factor. Can someone enlighten me to a
more obvious approach?
I don't think grouping on a factor is the source of your error. You have NA's
in your data and median will choke on those unless you specify na.rm=TRUE.
--
I thought the na.rm=TRUE in the aggregate function would do this (see above).
I also tried it with
medianRmNa - function(data) {
return(median(data, na.rm=TRUE))}
motifTable3 - aggregate.data.frame(motifTable2, by=list(motifTable2$events),
FUN=medianRmNa)
Error in median.default(data, na.rm = TRUE) : need numeric data
same error.
I did leave a line out of the above script,
names(motifTable) - c(events, freq)
which helps explain why the merge works
dhs
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[R] function in aggregate applied to specific columns only
I want to use aggregate with the mean function on specific columns gender - factor(c(m, m, f, f, m)) student - c(0001, 0002, 0003, 0003, 0001) score - c(50, 60, 70, 65, 60) basicSub - data.frame(student, gender, score) basicSubMean - aggregate(basicSub, by=list(basicSub$student), FUN=mean, na.rm=TRUE) This doesn't work, one cannot take the mean of a factor (gender). Is there any way of specifying which columns to use for the mean? I want to aggregate by student, obtaining mean scores, and assume any other factors are unchanging in a specific student, ie. gender. Thanks [[alternative HTML version deleted]] __ R-help@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.
