Re: [R] aggregate formula - differing results

On Mon, 4 Sep 2023, Ivan Calandra wrote: Thanks Rui for your help; that would be one possibility indeed. But am I the only one who finds that behavior of aggregate() completely unexpected and confusing? Especially considering that dplyr::summarise() and doBy::summaryBy() deal with NAs

Re: [R] aggregate formula - differing results

Ivan: Just one perhaps extraneous comment. You said that you were surprised that aggregate() and group_by() did not have the same behavior. That is a misconception on your part. As you know, the tidyverse recapitulates the functionality of many base R functions; but it makes no claims to do so in

Re: [R] aggregate formula - differing results

Haha, got it now, there is an na.action argument (which defaults to na.omit) to aggregate() which is applied before calling mean(na.rm = TRUE). Thank you Rui for pointing this out. So running it with na.pass instead of na.omit gives the same results as dplyr::group_by()+summarise():

Re: [R] aggregate formula - differing results

Às 12:51 de 04/09/2023, Ivan Calandra escreveu: Thanks Rui for your help; that would be one possibility indeed. But am I the only one who finds that behavior of aggregate() completely unexpected and confusing? Especially considering that dplyr::summarise() and doBy::summaryBy() deal with NAs

Re: [R] aggregate formula - differing results

Thanks Rui for your help; that would be one possibility indeed. But am I the only one who finds that behavior of aggregate() completely unexpected and confusing? Especially considering that dplyr::summarise() and doBy::summaryBy() deal with NAs differently, even though they all use mean(na.rm

Re: [R] aggregate formula - differing results

Às 10:44 de 04/09/2023, Ivan Calandra escreveu: Dear useRs, I have just stumbled across a behavior in aggregate() that I cannot explain. Any help would be appreciated! Sample data: my_data <- structure(list(ID = c("FLINT-1", "FLINT-10", "FLINT-100", "FLINT-101", "FLINT-102", "HORN-10",

Re: [R] aggregate formula - differing results

issing data. > > Iago > > *De:* R-help de part de Ivan Calandra > > *Enviat el:* dilluns, 4 de setembre de 2023 11:44 > *Per a:* R-help > *Tema:* [R] aggregate formula - differing results > Dear useRs, > &g

Re: [R] aggregate formula - differing results

it has no missing data. Iago De: R-help de part de Ivan Calandra Enviat el: dilluns, 4 de setembre de 2023 11:44 Per a: R-help Tema: [R] aggregate formula - differing results Dear useRs, I have just stumbled across a behavior in aggregate() that I cannot explain

[R] aggregate formula - differing results

Dear useRs, I have just stumbled across a behavior in aggregate() that I cannot explain. Any help would be appreciated! Sample data: my_data <- structure(list(ID = c("FLINT-1", "FLINT-10", "FLINT-100", "FLINT-101", "FLINT-102", "HORN-10", "HORN-100", "HORN-102", "HORN-103", "HORN-104"),

Re: [R] aggregate wind direction data with wind speed required

, Ancona (AN) Uff: +39 071 806 7743 E-mail: stefano.so...@regione.marche.it ---Oo-oO Da: Bill Dunlap Inviato: sabato 13 maggio 2023 22:38 A: Stefano Sofia Cc: r-help@R-project.org Oggetto: Re: [R] aggregate wind

Re: [R] aggregate wind direction data with wind speed required

You don't have to bother with the subtracting from pi/2 bit ... just assume the cartesian complex values are (y,x) instead of (x,y). On May 13, 2023 1:38:51 PM PDT, Bill Dunlap wrote: >I think that using complex numbers to represent the wind velocity makes >this simpler. You would need to

Re: [R] aggregate wind direction data with wind speed required

I think that using complex numbers to represent the wind velocity makes this simpler. You would need to write some simple conversion functions since wind directions are typically measured clockwise from north and the argument of a complex number is measured counterclockwise from east. E.g.,

Re: [R] aggregate wind direction data with wind speed required

Sorry Rui; if you run your code you will get: Error in FUN(X[[i]], ...) : object 'ws' not found Moreover, even if you did this: aggregate(wd ~ day + month, data=df, FUN = my_fun, ws1 = df$ws) the answer would be wrong is you need to include only the subsets of ws1 corresponding to the split

Re: [R] aggregate wind direction data with wind speed required

Às 15:51 de 13/05/2023, Stefano Sofia escreveu: Dear list users, I have to aggregate wind direction data (wd) using a function that requires also a second input variable, wind speed (ws). This is the function that I need to use: my_fun <- function(wd1, ws1){ u_component <-

[R] aggregate wind direction data with wind speed required

Dear list users, I have to aggregate wind direction data (wd) using a function that requires also a second input variable, wind speed (ws). This is the function that I need to use: my_fun <- function(wd1, ws1){ u_component <- -ws1*sin(2*pi*wd1/360) v_component <- -ws1*cos(2*pi*wd1/360)

Re: [R] aggregate semi-hourly data not 00-24 but 9-9

Da: Eric Berger [ericjber...@gmail.com] Inviato: martedì 22 settembre 2020 11.00 A: Jeff Newmiller Cc: Stefano Sofia; r-help mailing list Oggetto: Re: [R] aggregate semi-hourly data not 00-24 but 9-9 Thanks Jeff. Stefano, per Jeff's comment, you can

Re: [R] aggregate semi-hourly data not 00-24 but 9-9

Thanks Jeff. Stefano, per Jeff's comment, you can replace the line df1$data_POSIXminus9 <- df1$data_POSIX - lubridate::hours(9) by df1$data_POSIXminus9 <- df1$data_POSIX - as.difftime(9,units="hours") On Mon, Sep 21, 2020 at 8:06 PM Jeff Newmiller wrote: > > The base R as.difftime function is

Re: [R] aggregate semi-hourly data not 00-24 but 9-9

The base R as.difftime function is perfectly usable to create this offset without pulling in lubridate. On September 21, 2020 8:06:51 AM PDT, Eric Berger wrote: >Hi Stefano, >If you mean from 9am on one day to 9am on the following day, you can >do a trick. Simply subtract 9hrs from each

Re: [R] aggregate semi-hourly data not 00-24 but 9-9

Hi Stefano, If you mean from 9am on one day to 9am on the following day, you can do a trick. Simply subtract 9hrs from each timestamp and then you want midnight to midnight for these adjusted times, which you can get using the method you followed. I googled and found that lubridate::hours() can

[R] aggregate semi-hourly data not 00-24 but 9-9

Dear R-list members, I have semi-hourly snowfall data. I should sum the semi-hourly increments (only the positive ones, but this is not described in my example) day by day, not from 00 to 24 but from 9 to 9. I am able to use the diff function, create a list of days and use the function

Re: [R] Aggregate individual level data to age categories

Thank you! This is exactly what I was looking for! Cheers! On Wed, Feb 12, 2020 at 11:29 PM Jim Lemon wrote: > > Hi Stefan, > How about this: > > sddf<-read.table(text="age x > 45 1 > 45 2 > 46 1 > 47 3 > 47 3", > header=TRUE) > library(prettyR) > sdtab<-xtab(age~x,sddf) >

Re: [R] Aggregate individual level data to age categories

Hi Stefan, How about this: sddf<-read.table(text="age x 45 1 45 2 46 1 47 3 47 3", header=TRUE) library(prettyR) sdtab<-xtab(age~x,sddf) sdtab$counts Jim On Thu, Feb 13, 2020 at 7:40 AM stefan.d...@gmail.com wrote: > > Dear All, > > I have a seemingly standard problem to which I

Re: [R] Aggregate individual level data to age categories

Thank you, this is already very helpful. But how do I get it in the form age var_x=1 var_x=2 var_x=3 45 1 1 0 46 1 00 So it would be a data frame with 4 variables. Cheers! On Wed, Feb 12, 2020 at 10:25 PM William Dunlap wrote: > >

Re: [R] Aggregate individual level data to age categories

You didn't say how you wanted to use it as a data.frame, but here is one way d <- data.frame( check.names = FALSE, age = c(45L, 45L, 46L, 47L, 47L), x = c(1L, 2L, 1L, 3L, 3L)) with(d, as.data.frame(table(age,x))) which gives: age x Freq 1 45 11 2 46 11 3 47 10 4 45

Re: [R] Aggregate individual level data to age categories

well, if I think about, its actually a simple frequency table grouped by age. but it should be usable a matrix or data frame. On Wed, Feb 12, 2020 at 9:48 PM wrote: > > So a pivot table? > > On 12 Feb 2020 20:39, stefan.d...@gmail.com wrote: > > Dear All, > > I have a seemingly standard problem

[R] Aggregate individual level data to age categories

Dear All, I have a seemingly standard problem to which I somehow I do not find a simple solution. I have individual level data where x is a categorical variable with 3 categories which I would like to aggregate by age. age x 45 1 45 2 46 1 47 3 47 3 and so on. It should after

Re: [R] aggregate output to data frame

You can also use 'dplyr' library(tidyverse) result <- pcr %>% group_by(Gene, Type, Rep) %>% summarise(mean = mean(Ct), sd = sd(Ct), oth = sd(Ct) / sqrt(sd(Ct)) ) Jim Holtman *Data Munger Guru* *What is the problem that you are trying to solve?Tell me

Re: [R] aggregate output to data frame

Hi Cyrus, Try this: pcr<-data.frame(Ct=runif(66,10,20),Gene=rep(LETTERS[1:22],3), Type=rep(c("Std","Unkn"),33),Rep=rep(1:3,each=22)) testagg<-aggregate(pcr$Ct,c(pcr["Gene"],pcr["Type"],pcr["Rep"]), FUN=function(x){c(mean(x), sd(x), sd(x)/sqrt(sd(x)))}) nxcol<-dim(testagg$x)[2]

[R] aggregate output to data frame

Dear users, i am trying to summarize data using "aggregate" with the following command: aggregate(pcr$Ct,c(pcr["Gene"],pcr["Type"],pcr["Rep"]),FUN=function(x){c(mean(x), sd(x), sd(x)/sqrt(sd(x)))}) and the structure of the resulting data frame is 'data.frame':66 obs. of  4 variables: $

Re: [R] aggregate and list elements of variables in data.frame

Hi, if you are willing to use dplyr, you can do all in one line of code: library(dplyr) df<-data.frame(id=1:10,A=c(123,345,123,678,345,123,789,345,123,789)) df%>%group_by(unique_A=A)%>%summarise(list_id=paste(id,collapse=", "))->r cheers Am 06.06.2018 um 10:13 schrieb Massimo Bressan: >

Re: [R] aggregate and list elements of variables in data.frame

which() is unnecessary. Use logical subscripting: ... t$id[t$A ==x] Further simplification can be gotten by using the with() function: l <- with(t, sapply(unique(A), function(x) id[A ==x])) Check this though -- there might be scoping issues. Cheers, Bert On Thu, Jun 7, 2018, 6:49 AM

Re: [R] aggregate and list elements of variables in data.frame

#ok, finally this is my final "best and more compact" solution of the problem by merging different contributions (thanks to all indeed) t<-data.frame(id=c(18,91,20,68,54,27,26,15,4,97),A=c(123,345,123,678,345,123,789,345,123,789)) l<-sapply(unique(t$A), function(x) t$id[which(t$A==x)])

Re: [R] aggregate and list elements of variables in data.frame

- lapply(idx, function(index) x$id[index]) data.frame(unique_A = uA, list_vals=unlist(lapply(vals, paste, collapse = ", "))) best Da: "Ben Tupper" A: "Massimo Bressan" Cc: "r-help" Inviato: Giovedì, 7 giugno 2018 14:47:55 Oggetto: Re: [R] aggrega

Re: [R] aggregate and list elements of variables in data.frame

Hi, Does this do what you want? I had to change the id values to something more obvious. It uses tibbles which allow each variable to be a list. library(tibble) library(dplyr) x <- tibble(id=LETTERS[1:10], A=c(123,345,123,678,345,123,789,345,123,789)) uA <-

Re: [R] aggregate and list elements of variables in data.frame

Using which() to subset t$id should do the trick: sapply(levels(t$A), function(x) t$id[which(t$A==x)]) Ivan -- Dr. Ivan Calandra TraCEr, laboratory for Traceology and Controlled Experiments MONREPOS Archaeological Research Centre and Museum for Human Behavioural Evolution Schloss Monrepos

Re: [R] aggregate and list elements of variables in data.frame

sorry, but by further looking at the example I just realised that the posted solution it's not completely what I need because in fact I do not need to get back the 'indices' but instead the corrisponding values of column A #please consider this new example

Re: [R] aggregate and list elements of variables in data.frame

thanks for the help I'm posting here the complete solution t<-data.frame(id=1:10,A=c(123,345,123,678,345,123,789,345,123,789)) t$A <- factor(t$A) l<-sapply(levels(t$A), function(x) which(t$A==x)) r<-data.frame(list_id=unlist(lapply(l, paste, collapse = ", ")))

Re: [R] aggregate and list elements of variables in data.frame

Hi Massimo, Something along those lines could help you I guess: t$A <- factor(t$A) sapply(levels(t$A), function(x) which(t$A==x)) You can then play with the output using paste() Ivan -- Dr. Ivan Calandra TraCEr, laboratory for Traceology and Controlled Experiments MONREPOS Archaeological

[R] aggregate and list elements of variables in data.frame

#given the following reproducible and simplified example t<-data.frame(id=1:10,A=c(123,345,123,678,345,123,789,345,123,789)) t #I need to get the following result r<-data.frame(unique_A=c(123, 345, 678, 789),list_id=c('1,3,6,9','2,5,8','4','7,10')) r # i.e. aggregate over the variable

Re: [R] Aggregate over multiple and unequal column length data frames

Thank you again Pikal and Bert. Using lapply, as Bert suggested, was the first thing that i thought of dealing with this question and was mentioned in my original posting. I just did not know how to implement it to get the results/form i want. Below is what i did but could not get it to give me

Re: [R] Aggregate over multiple and unequal column length data frames

could try to aggregate them somehow. > > > > I could construct example data.frames myself but most probably they > would be different from yours and also the result would not be necessary > the same as you expect. > > > > You should post those data frames as output fr

Re: [R] Aggregate over multiple and unequal column length data frames

1 0 0 I believe that in your dfn is typo in second row and first column and that with your 3 data.frames the result should be 1. Cheers Petr > -Original Message- > From: Ek Esawi [mailto:esaw...@gmail.com] > Sent: Tuesday, February 27, 2018 2:54 PM > To: PIKAL Petr <petr.pi..

Re: [R] Aggregate over multiple and unequal column length data frames

ta.frames myself but most probably they would be > different from yours and also the result would not be necessary the same as > you expect. > > You should post those data frames as output from dput(data) and show us real > desired result from those example data frames. > > Cheer

Re: [R] Aggregate over multiple and unequal column length data frames

r-help-boun...@r-project.org] On Behalf Of Ek Esawi > Sent: Wednesday, February 21, 2018 3:34 AM > To: r-help@r-project.org > Subject: [R] Aggregate over multiple and unequal column length data frames > > Hi All-- > > I have generated several 2 column data frames with variable len

Re: [R] Aggregate over multiple and unequal column length data frames

All columns in a data.frame **must** have the same length. So you cannot do this unless empty values are filled with missings (NA's). -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his

[R] Aggregate over multiple and unequal column length data frames

Hi All-- I have generated several 2 column data frames with variable length. The data frames have the same column names and variable types. I was trying to aggregate over the 2nd column for all the date frames, but could not figure out how. I thought i could make them all of equal length then

Re: [R] Aggregate behaviour inconsistent (?) when FUN=table

Thank you for your response. Note that with R 3.4.3, I get the same result with simplify=TRUE or simplify=FALSE. My problem was the behaviour was different if I define my columns as character or as numeric but for now some minutes I discovered there also is a stringsAsFactors option in the

Re: [R] Aggregate behaviour inconsistent (?) when FUN=table

Don't use aggregate's simplify=TRUE when FUN() produces return values of various dimensions. In your case, the shape of table(subset)'s return value depends on the number of levels in the factor 'subset'. If you make B a factor before splitting it by C, each split will have the same number of

Re: [R] Aggregate behaviour inconsistent (?) when FUN=table

The normal input to a factory that builds cars is car parts. Feeding whole trucks into such a factory is likely to yield odd-looking results. Both aggregate and table do similar kinds of things, but yield differently constructed outputs. The output of the table function is not well-suited to be

[R] Aggregate behaviour inconsistent (?) when FUN=table

Dear R users, When I use aggregate with table as FUN, I get what I would call a strange behaviour if it involves numerical vectors and one "level" of it is not present for every "levels" of the "by" variable: --- > df <-

Re: [R] Aggregate counts of observations with times surrounding a time?

Hi again, Here is a version cleaned up a bit. Too tired to do it last night. mndf<-data.frame(st=seq(1483360938,by=1700,length=10), et=seq(1483362938,by=1700,length=10), store=c(rep("gap",5),rep("starbucks",5)), zip=c(94000,94000,94100,94100,94200,94000,94000,94100,94100,94200),

Re: [R] Aggregate counts of observations with times surrounding a time?

Hi Mark, I think you might want something like this: mndf<-data.frame(st=seq(1483360938,by=1700,length=10), et=seq(1483362938,by=1700,length=10), store=c(rep("gap",5),rep("starbucks",5)), zip=c(94000,94000,94100,94100,94200,94000,94000,94100,94100,94200), store_id=seq(50,59)) # orders the

[R] Aggregate counts of observations with times surrounding a time?

I have a data frame that has a set of observed dwell times at a set of locations. The metadata for the locations includes things that have varying degrees of specificity. I'm interested in tracking the number of people present at a given time in a given store, type of store, or zip code. Here's

Re: [R] Aggregate data to lower resolution

= c(-54.75, >>> -54.75, -54.75, -54.25, -54.25, -54.25, -53.75, -53.75, -53.75, >>> -53.75), GDP = c(1.683046, 0.3212307, 0.0486207, 0.1223268, 0.0171909, >>> 0.0062104, 0.22379, 0.1406729, 0.0030038, 0.0057422)), .Names = >>> c("longitude", >>>

Re: [R] aggregate dataframe by multiple factors

2016 at 11:34 AM, PIKAL Petr <petr.pi...@precheza.cz> > wrote: > > >>> Hi > > >>> > > >>> same result can be achieved by > > >>> > > >>> dat.ag<-aggregate(dat[ , c("DCE","DP")], by= list(dat$first.Nam

Re: [R] aggregate dataframe by multiple factors

DCE","DP")], by= list(dat$first.Name, > >>> dat$Name, dat$Department) , "I") > >>> > >>> Sorting according to the first row seems to be quite tricky. You could > >>> probably get closer by using some combination of split

Re: [R] aggregate dataframe by multiple factors

t; >>> > >>> Sorting according to the first row seems to be quite tricky. You could > probably get closer by using some combination of split and order and > arranging back chunks of data > >>> > >>> ooo1<-order(split(dat$DCE,interaction(dat$fir

Re: [R] aggregate dataframe by multiple factors

>>> >>> ooo1<-order(split(dat$DCE,interaction(dat$first.Name, dat$Name, >>> dat$Department, drop=T))[[1]]) >>> data.frame(sapply(split(dat$DCE,interaction(dat$first.Name, dat$Name, >>> dat$Department, drop=T)), rbind))[ooo1,] >>> Ancient.Nation.QLH

Re: [R] aggregate dataframe by multiple factors

s.TAS Auction.Videos.YME > > 2 0.28 NA NA > > 4 0.28 NA NA > > 1 0.540.59 0.57 > > 3 0.540.59 0.57 > > >

Re: [R] aggregate dataframe by multiple factors

; > > however I wonder why the order according to the first row is necessary > if all NAs are on correct positions? > > > > Cheers > > Petr > > > > > > > -Original Message- > > > From: R-help [mailto:r-help-boun...@r-proj

Re: [R] aggregate dataframe by multiple factors

---Original Message----- > > From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of David > > Winsemius > > Sent: Friday, November 18, 2016 9:30 AM > > To: Karim Mezhoud <kmezh...@gmail.com> > > Cc: r-help@r-project.org > > Subject: Re: [R] aggregate d

Re: [R] aggregate dataframe by multiple factors

n...@r-project.org] On Behalf Of David > > Winsemius > > Sent: Friday, November 18, 2016 9:30 AM > > To: Karim Mezhoud <kmezh...@gmail.com> > > Cc: r-help@r-project.org > > Subject: Re: [R] aggregate dataframe by multiple factors > > > > > > > On Nov 17

Re: [R] aggregate dataframe by multiple factors

necessary if all NAs are on correct positions? Cheers Petr > -Original Message- > From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of David > Winsemius > Sent: Friday, November 18, 2016 9:30 AM > To: Karim Mezhoud <kmezh...@gmail.com> > Cc: r-help@r-pr

Re: [R] aggregate dataframe by multiple factors

> On Nov 17, 2016, at 11:27 PM, Karim Mezhoud wrote: > > Dear all, > > the dat has missing values NA, > >first.Name Name Department DCE DP date > 5 Auction VideosYME 0.57 0.56 2013-09-30 > 18 Amish WivesTAS 0.59 0.56 2013-09-30 >

[R] aggregate dataframe by multiple factors

Dear all, the dat has missing values NA, first.Name Name Department DCE DP date 5 Auction VideosYME 0.57 0.56 2013-09-30 18 Amish WivesTAS 0.59 0.56 2013-09-30 34 Ancient NationQLH 0.54 0.58 2013-09-30 53 Auction VideosYME NA

Re: [R] aggregate

2.1 S1 B > S2A 38 3.2 S2 A > S2B 22 3.2 S2 B > > David C > > -Original Message- > From: Gang Chen [mailto:gangch...@gmail.com] > Sent: Wednesday, August 24, 2016 2:51 PM > To: David L Carlson > Cc: r-help mailing list > Subject: Re: [R] aggregate > > Thank

Re: [R] aggregate

t Subject: Re: [R] aggregate Thanks again for patiently offering great help, David! I just learned dput() and paste0() now. Hopefully this is my last question. Suppose a new dataframe is as below (one more numeric column): myData <- structure(list(X = c(1, 2, 3, 4, 5, 6, 7, 8), Y = c(8, 7, 6, 5

Re: [R] aggregate

els just requires the paste0() function: > >> sapply(split(myData, paste0(myData$S, myData$Z)), function(x) crossprod(x[, >> 1], x[, 2])) > S1A S1B S2A S2B > 22 38 38 22 > > David C > > -Original Message- > From: Gang Chen [mailto:gangch...@gmail.co

Re: [R] aggregate

22 David C -Original Message- From: Gang Chen [mailto:gangch...@gmail.com] Sent: Wednesday, August 24, 2016 11:56 AM To: David L Carlson Cc: Jim Lemon; r-help mailing list Subject: Re: [R] aggregate Thanks a lot, David! I want to further expand the operation a little bit. With a new dat

Re: [R] aggregate

tion(x) crossprod(x[, 1], x[, 2]))) > Z CP > A A 10 > B B 10 > > David C > > > -Original Message- > From: Gang Chen [mailto:gangch...@gmail.com] > Sent: Wednesday, August 24, 2016 10:17 AM > To: David L Carlson > Cc: Jim Lemon; r-help mailing list >

Re: [R] aggregate

com] Sent: Wednesday, August 24, 2016 10:17 AM To: David L Carlson Cc: Jim Lemon; r-help mailing list Subject: Re: [R] aggregate Thank you all for the suggestions! Yes, I'm looking for the cross product between the two columns of X and Y. A follow-up question: what is a nice way to merge the out

Re: [R] aggregate

gt; College Station, TX 77840-4352 > > > -Original Message- > From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Jim Lemon > Sent: Tuesday, August 23, 2016 6:02 PM > To: Gang Chen; r-help mailing list > Subject: Re: [R] aggregate > > Hi Gang Che

Re: [R] aggregate

L Carlson Department of Anthropology Texas A University College Station, TX 77840-4352 -Original Message- From: R-help [mailto:r-help-boun...@r-project.org] On Behalf Of Jim Lemon Sent: Tuesday, August 23, 2016 6:02 PM To: Gang Chen; r-help mailing list Subject: Re: [R] aggregate H

Re: [R] aggregate

Hi Gang Chen, If I have the right idea: for(zval in levels(myData$Z)) crossprod(as.matrix(myData[myData$Z==zval,c("X","Y")])) Jim On Wed, Aug 24, 2016 at 8:03 AM, Gang Chen wrote: > This is a simple question: With a dataframe like the following > > myData <-

Re: [R] aggregate

> On Aug 23, 2016, at 3:03 PM, Gang Chen wrote: > > This is a simple question: With a dataframe like the following > > myData <- data.frame(X=c(1, 2, 3, 4), Y=c(4, 3, 2, 1), Z=c('A', 'A', 'B', > 'B')) > > how can I get the cross product between X and Y for each level of

[R] aggregate

This is a simple question: With a dataframe like the following myData <- data.frame(X=c(1, 2, 3, 4), Y=c(4, 3, 2, 1), Z=c('A', 'A', 'B', 'B')) how can I get the cross product between X and Y for each level of factor Z? My difficulty is that I don't know how to deal with the fact that crossprod()

Re: [R] Aggregate matrix in a 2 by 2 manor

efine the dimensions of my >>>>> a <- array( m >>>>> , dim = c( ny >>>>> , nrow( m ) %/% ny >>>>> , ncol( m ) %/% nx ) >>>>> ) >>>>> # apply mean over di

Re: [R] Aggregate matrix in a 2 by 2 manor

y College Station, TX 77840-4352 -Original Message- From: R-help [mailto:r-help-boun...@r-poject.org] On Behalf Of Anthoni, Peter (IMK) Sent: Wednesday, July 27, 2016 6:14 AM To: r-help@r-project.org Subject: [R] Aggregate matrix in a 2 by 2 manor Hi all, I need to aggregate some mat

Re: [R] Aggregate matrix in a 2 by 2 manor

. It uses apply() across the blocks. >>>> >>>>> ilon <- seq(1,8,nx) >>>>> ilat <- seq(1,4,ny) >>>>> cells <- as.matrix(expand.grid(ilat, ilon)) >>>>> blocks <- apply(cells, 1, function(x) tst[x[1]:(x[1]+

Re: [R] Aggregate matrix in a 2 by 2 manor

t; tst_2x2 <- matrix(block.means, 2, 4) >>>> tst_2x2 >>> [,1] [,2] [,3] [,4] >>> [1,] 3.5 11.5 19.5 27.5 >>> [2,] 5.5 13.5 21.5 29.5 >>> >>> - >>> David L Carlson >>> Department of

Re: [R] Aggregate matrix in a 2 by 2 manor

2 >>[,1] [,2] [,3] [,4] >> [1,] 3.5 11.5 19.5 27.5 >> [2,] 5.5 13.5 21.5 29.5 >> >> - >> David L Carlson >> Department of Anthropology >> Texas A University >> College Station, TX 77840-4352 >> &g

Re: [R] Aggregate matrix in a 2 by 2 manor

inal Message- >From: R-help [mailto:r-help-boun...@r-poject.org] On Behalf Of Anthoni, >Peter (IMK) >Sent: Wednesday, July 27, 2016 6:14 AM >To: r-help@r-project.org >Subject: [R] Aggregate matrix in a 2 by 2 manor > >Hi all, > >I need to aggregate some matrix data (1

Re: [R] Aggregate matrix in a 2 by 2 manor

elp [mailto:r-help-boun...@r-poject.org] On Behalf Of Anthoni, Peter (IMK) Sent: Wednesday, July 27, 2016 6:14 AM To: r-help@r-project.org Subject: [R] Aggregate matrix in a 2 by 2 manor Hi all, I need to aggregate some matrix data (1440x720) to a lower dimension (720x360) for lots of years

[R] Aggregate matrix in a 2 by 2 manor

Hi all, I need to aggregate some matrix data (1440x720) to a lower dimension (720x360) for lots of years and variables I can do double for loop, but that will be slow. Anybody know a quicker way? here an example with a smaller matrix size: tst=matrix(1:(8*4),ncol=8,nrow=4)

Re: [R] Aggregate data to lower resolution

ot;), row.names = c(4L, 17L, 30L, 43L, 56L, 69L, >> 82L, 95L, 108L, 121L), class = "data.frame") >> >> I would like to aggregate the data 1 degree by 1 degree. I understand that >> the first step is to convert to raster. I have tried: >> >> rasterD

Re: [R] Aggregate data to lower resolution

ot;) > > I would like to aggregate the data 1 degree by 1 degree. I understand that > the first step is to convert to raster. I have tried: > > rasterDF <- rasterFromXYZ(temp) > r <- aggregate(rasterDF,fact=2, fun=sum) > > But this does not seem to wor

[R] Aggregate data to lower resolution

ass = "data.frame") I would like to aggregate the data 1 degree by 1 degree. I understand that the first step is to convert to raster. I have tried: rasterDF <- rasterFromXYZ(temp) r <- aggregate(rasterDF,fact=2, fun=sum) But this does not seem to work. Could anyone help me ou

Re: [R] Aggregate rainfall data

Hi David, Thank you so much for your help and others. Here is the code. balok <- read.csv("G:/A_backup 11 mei 2015/DATA (D)/1 Universiti Malaysia Pahang/ISM-3 2016 UM/Data/Hourly Rainfall/balok2.csv",header=TRUE) head(balok, 10); tail(balok, 10) str(balok) ## Introduce NAs for balok$Rain.mm2

Re: [R] Aggregate rainfall data

> On Jul 13, 2016, at 3:21 AM, roslinazairimah zakaria > wrote: > > Dear David, > > I got your point. How do I remove the data that contain "0.0?". > > I tried : balok <- cbind(balok3[,-5], balok3$Rain.mm[balok3$Rain.mm==0.0?] <- > NA) If you had done as I suggested,

Re: [R] Aggregate rainfall data

Behalf Of > roslinazairimah zakaria > Sent: Wednesday, July 13, 2016 12:22 PM > To: David Winsemius <dwinsem...@comcast.net> > Cc: r-help mailing list <r-help@r-project.org> > Subject: Re: [R] Aggregate rainfall data > > Dear David, > > I got your point.

Re: [R] Aggregate rainfall data

use `gsub()` after the `as.character()` conversion to remove everything but valid numeric components from the strings. On Wed, Jul 13, 2016 at 6:21 AM, roslinazairimah zakaria wrote: > Dear David, > > I got your point. How do I remove the data that contain "0.0?". > > I

Re: [R] Aggregate rainfall data

Dear David, I got your point. How do I remove the data that contain "0.0?". I tried : balok <- cbind(balok3[,-5], balok3$Rain.mm[balok3$Rain.mm==0.0?] <- NA) However all the Rain.mm column all become NA. day month year Time balok3$Rain.mm[balok3$Rain.mm == "0.0?"] <- NA 1 30 7

Re: [R] Aggregate rainfall data

> On Jul 12, 2016, at 3:45 PM, roslinazairimah zakaria > wrote: > > Dear R-users, > > I have these data: > > head(balok, 10); tail(balok, 10) >Date Time Rain.mm > 1 30/7/2008 9:00:00 0 > 2 30/7/2008 10:00:00 0 > 3 30/7/2008 11:00:00 0 >

[R] Aggregate rainfall data

Dear R-users, I have these data: head(balok, 10); tail(balok, 10) Date Time Rain.mm 1 30/7/2008 9:00:00 0 2 30/7/2008 10:00:00 0 3 30/7/2008 11:00:00 0 4 30/7/2008 12:00:00 0 5 30/7/2008 13:00:00 0 6 30/7/2008 14:00:00 0 7 30/7/2008

Re: [R] Aggregate FIPS data to State and Census divisions

> On May 1, 2016, at 9:30 AM, Miluji Sb wrote: > > Dear Dennis, > > Thank you for your reply. I can use the dplyr/data.table packages to > aggregate - its the matching FIPS codes to their states that I am having > trouble. Thanks again. So post some example code that

Re: [R] Aggregate FIPS data to State and Census divisions

Dear Dennis, Thank you for your reply. I can use the dplyr/data.table packages to aggregate - its the matching FIPS codes to their states that I am having trouble. Thanks again. Sincerely, Milu On Sun, May 1, 2016 at 6:20 PM, Dennis Murphy wrote: > Hi: > > Several such

[R] Aggregate FIPS data to State and Census divisions

Dear all, I have the following data by US FIPS code. Is there a package to aggregate the data by State and Census divisions? temp <- dput(head(pop1,5)) structure(list(FIPS = c("01001", "01003", "01005", "01007", "01009" ), death_2050A1 = c(18.19158, 101.63088, 13.18896, 10.30068, 131.91798),

Re: [R] aggregate combination data

Hello, I'm cc'ing R-Help. Sorry but your question was asked 3.5 years ago, I really don't remember it. Can you please post a question to R-Help, with a reproducible example that describes your problem? Rui Barradas   Citando catalin roibu : > Dear Rui, >   > I

Re: [R] aggregate and the $ operator

So that's how that works! Thanks. On Fri, Jan 22, 2016 at 1:32 PM, Joe Ceradini wrote: > Does this do what you want? > > aggregate(Nuclei ~ Slide, example, sum) > > On Fri, Jan 22, 2016 at 12:20 PM, Ed Siefker wrote: >> >> Aggregate does the right

Re: [R] aggregate and the $ operator

Using column names where you used column numbers would work: example <- data.frame( check.names = FALSE, Nuclei = c(133L, 96L, 62L, 60L), `Positive Nuclei` = c(96L, 70L, 52L, 50L), Slide = factor(c("A1", "A1", "A2", "A2"), levels = c("A1", "A2"))) aggregate(example["Nuclei"],

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