Hi Miluj,
Perhaps you didn't get my previous email. Let your data frame be named "msdf":
block_col_summ<-function(x,step,block_size,FUN="mean") {
dimx<-dim(x)
return_value<-NA
start<-1
end<-start+block_size-1
block_count<-1
while(end <= dimx[2]) {
return_value[block_count]<-
do.call(FUN,list(as.matrix(x[,start:end]),na.rm=TRUE))
block_count<-block_count+1
start<-start+step
end<-start+block_size-1
}
return(return_value)
}
# use the step and block size that you want
block_col_summ(msdf,4,4)
Jim
On Thu, Nov 10, 2016 at 3:29 AM, Miluji Sb <miluj...@gmail.com> wrote:
> Dear all,
>
> I have a dataset with hundreds of columns, I am only providing only 12
> columns. Is it possible to take the mean of every four (or 12) columns
> (value601, value602, value603, value604 etc.in this case) and repeat for
> the hundreds of columns? Thank you.
>
> Sincerely,
>
> Milu
>
> structure(list(value601 = c(10.1738710403442, 3.54112911224365,
> 12.9192342758179, 3.17447590827942, 11.7332258224487, 7.68282270431519,
> -7.11564493179321, 0.987620949745178, 13.0476207733154, 6.36939525604248
> ), value602 = c(13.0642414093018, 5.53129482269287, 16.0519638061523,
> 2.88946437835693, 14.9204912185669, 9.42428588867188, -6.80674123764038,
> -0.614241063594818, 16.7947769165039, 7.9541072845459), value603 =
> c(22.0399188995361,
> 14.398024559021, 24.9523792266846, 12.0878629684448, 23.6459674835205,
> 18.3277816772461, -2.54092741012573, 10.5550804138184, 25.1016540527344,
> 16.2166938781738), value604 = c(27.7165412902832, 20.3255825042725,
> 30.8430004119873, 16.6856250762939, 29.2485408782959, 24.3775005340576,
> 6.47758340835571, 15.5897912979126, 30.7387924194336, 22.3637084960938
> ), value605 = c(31.6644763946533, 23.4093952178955, 35.1488723754883,
> 19.7132263183594, 33.3924179077148, 29.5846366882324, 10.2083873748779,
> 19.3551616668701, 35.3076629638672, 27.4299201965332), value606 =
> c(33.9698333740234,
> 26.8574161529541, 36.8900833129883, 22.8604583740234, 34.8642921447754,
> 33.8158760070801, 14.7055835723877, 22.1144580841064, 37.0545425415039,
> 32.1087913513184), value607 = c(36.0279846191406, 26.9297180175781,
> 38.2701225280762, 23.2643146514893, 36.7398796081543, 34.1216125488281,
> 17.1387901306152, 24.0419750213623, 37.8542327880859, 32.7677421569824
> ), value608 = c(34.0242347717285, 25.7720966339111, 36.4897193908691,
> 22.0332260131836, 34.8011703491211, 32.6856842041016, 16.6232261657715,
> 21.5571365356445, 36.1491546630859, 31.1716938018799), value609 =
> c(27.5402088165283,
> 21.7590408325195, 30.5214176177979, 18.4252090454102, 29.1156253814697,
> 26.9878330230713, 12.4962501525879, 17.7259578704834, 30.9099159240723,
> 25.4832077026367), value610 = c(23.4706859588623, 17.0126209259033,
> 26.8166942596436, 15.297459602356, 25.1733055114746, 23.5616931915283,
> 8.86995983123779, 13.5793552398682, 27.5732250213623, 22.1691932678223
> ), value611 = c(14.5820417404175, 9.08279132843018, 17.8419170379639,
> 8.36016654968262, 16.5633754730225, 14.8123331069946, 1.32095837593079,
> 5.73408317565918, 18.9752082824707, 13.5729999542236), value612 =
> c(9.12979793548584,
> 2.79943537712097, 11.6504030227661, 2.21584677696228, 10.5404834747314,
> 7.55471754074097, -5.58141136169434, -0.566209673881531, 12.3264112472534,
> 6.65576601028442)), .Names = c("value601", "value602", "value603",
> "value604", "value605", "value606", "value607", "value608", "value609",
> "value610", "value611", "value612"), row.names = c("1", "2",
> "3", "4", "5", "6", "7", "8", "9", "10"), class = "data.frame")
>
> [[alternative HTML version deleted]]
>
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