I was wondering about the layout of each of your data sets. I cobbled together what I think is the most likely scenarios. My bet is the data sets most closely resemble my data set 4 in structure. Am I correct? I dropped the other two columns in your data layout as likely to be immaterial to the problem.
data set 1 (unique text and class) class text 0 text1 2 text2 1 text3 2 text4 data set 2 (unique class, multiple text) class text 0 text1 0 text1 0 text1 2 text2 1 text3 2 text4 data set 3 (multiple classes, multiple text) class text 0 text1 0 text1 1 text1 2 text2 1 text3 2 text4 data set 4 (mutltiple classes , multiple text, text not found in other data sets) 0 text1 0 text1 1 text1 2 text2 1 text3 2 text4 2 text6 0 text6 John Kane Kingston ON Canada > -----Original Message----- > From: mxalimoha...@ualr.edu > Sent: Tue, 26 May 2015 20:11:08 -0500 > To: r-help@r-project.org > Subject: Re: [R] Problem with comparing multiple data sets > > Thank you John. Yes. as you mentioned this is not really what I am > looking > for. > > It's interesting because I was really thinking that it should be pretty > easy. All I need to do is just compare class1, class2 and class3 for each > text and put the most frequent number next to it in each row. Repeat it > for > all the rows. Apparently it's not that simple. > > Sorry I didn't notice that I sent it only to you! Thanks for letting me > know. > > I appreciate if anybody can help on this. > > Thank you. > > > > > On Tue, May 26, 2015 at 7:27 PM, John Kane <jrkrid...@inbox.com> wrote: > >> Hi Mohammad, >> >> The data came through beautifully despite the fact that you posted in >> HTML. Please, post in plain text. >> >> Oh, just as I was ready to push Send, I noticed you only replied to me. >> You really should reply to the R-help list since there are a lot more >> and >> better people to help there. Besides it's a world-wide list. Others can >> play with the problem while we sleep :) . >> >> I will just reply to you but I really suggest sending all of this to the >> list. >> >> Now I am wondering what to do with the data. As a first swipe I just >> added >> up all the values in each class by each text value. Results are below. >> Not >> what you want by any means but perhaps a small step. >> >> Then I started to think are we really interested in the sum or should we >> be looking at incidence, that is should we be looking at the frequency >> rather than the sum? >> >> Is >> class.1 class.2 class #dac >> 0 2 0 >> >> a value of 2 (sum) or a hit of 1 (count or freq) ? >> >> Anyway below is what I have tried so far -- it may not be anywhere near >> what you want but if it makes any sense then I think we just need to >> pick >> off the highest values for each combination of terms and class to give >> you >> what you want. >> >> I suspect our real data-munging gurus can do all this faster and better >> than I can but hopefully it is a start. >> >> Where your data set is dat1 >> #===================================== >> # If reshape2 is not installed. >> install.packages("reshape2") >> #===================================== >> >> library(reshape2) >> mdat <- melt(dat1, id.vars= c("terms"), >> variable.name = "class", >> value.name = "value", >> na.rm = FALSE) >> >> mdat1 <- aggregate(value ~ terms + class, data = mdat, sum) >> >> mdat1[order(mdat1$terms, mdat1$class), ] >> >> #===================================== >> >> >> John Kane >> Kingston ON Canada >> >> -----Original Message----- >> From: mxalimoha...@ualr.edu >> Sent: Tue, 26 May 2015 09:50:43 -0500 >> To: jrkrid...@inbox.com >> Subject: Re: [R] Problem with comparing multiple data sets >> >> Thank you John for being patient with me. >> >> My original post was to compare 3 sets of data which had difference in >> their class value for the same text. However, I thought it might be >> easier >> to combine those 3 data sets into one that shows the 3 different classes >> and then find the most frequent class value for the text. So that's what >> I >> did. Now I only want to add the most frequent class value in a new >> column. >> >> I tried to create a dput version of the data set (Only a small part of >> it) >> so you can see. I hope it works. >> >>> Tweet1<- read.csv(file="part1_complete.csv",head=TRUE,sep= ",") >> >>> dput(head(Tweet1, 100)) >> >> structure(list(class.1 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 1L, 1L, 1L, >> >> 1L, 2L, 2L, 1L, 1L, 2L, 1L, 2L, 0L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, >> >> 1L, 2L, 1L, 1L, 1L, 0L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, >> >> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >> >> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L), class.2 = c(2L, >> >> 2L, 2L, 2L, 0L, 0L, 2L, 0L, 0L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, >> >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> >> 2L, 0L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 0L, 0L, 0L, 0L, 1L, 1L, 1L, >> >> 0L, 1L, 1L, 1L, 0L, 1L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 0L, >> >> 1L, 0L, 0L, 1L, 0L, 0L, 1L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, >> >> 1L, 1L, 2L, 2L, 2L, 1L, 1L, 1L, 0L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, >> >> 1L, 1L, 1L), class.3 = c(0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, >> >> 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 1L, 1L, 1L, >> >> 1L, 0L, 0L, 0L, 0L, 2L, 1L, 2L, 0L, 2L, 2L, 0L, 2L, 1L, 1L, 1L, >> >> 1L, 0L, 0L, 0L, 2L, 1L, 0L, 0L, 1L, 0L, 0L, 2L, 2L, 2L, 2L, 2L, >> >> 0L, 2L, 2L, 1L, 0L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, >> >> 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L), terms = structure(c(9L, >> >> 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, >> >> 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, >> >> 9L, 9L, 9L, 9L, 69L, 69L, 69L, 69L, 69L, 40L, 40L, 40L, 40L, >> >> 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 98L, 98L, 98L, 98L, 98L, >> >> 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 98L, 23L, 87L, 87L, 87L, >> >> 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, >> >> 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, 87L, >> >> 87L, 87L), .Label = c("#accountability", >> "#accountability,#anonymity,anonymity", >> >> "#accountability,recovery", "#anonymity,anonymity", >> "#anonymous,anonymous", >> >> "#attacker,security", "#authentication,access control", "#confidential", >> >> "#dac", "#encryption,#privacy,#security", "#identifier", >> "#identifier,identifier", >> >> "#intrusion,#security,security", "#mac", "#mac,#security", >> "#mac,password", >> >> "#mac,security", "#password,privacy", "#password,security", >> "#prevention,prevention", >> >> "#privacy,#security,password", "#privacy,identifiable", >> "#privacy,information privacy,privacy", >> >> "#privacy,intrusion", "#privacy,location privacy,privacy", >> "#privacy,password,security", >> >> "#privacy,personal data", "#privacy,personal information,privacy", >> >> "#privacy,security", "#pseudonym", "#pseudonymity", >> "#security,authentication,identity management", >> >> "#security,identity management,security", "#security,mac,security", >> >> "#security,malicious,security", "#security,personal information", >> >> "#security,retention", "#token", "#token,token", >> "accountability,anonymous", >> >> "accountability,audit trail", "accountability,confidential", >> >> "accountability,security", "accountability,token", "adversary,pin", >> >> "anonymity,authentication", "anonymity,security", >> "anonymous,disclosure", >> >> "anonymous,password", "authentication,password,security", >> "authorization,mac", >> >> "authorization,permission", "confidential,disclosure", >> "confidential,disclosure,security", >> >> "confidential,mac", "confidential,personal information", >> "confidential,pin", >> >> "confidential,privilege", "confidentiality,security", "consent", >> >> "dac", "dac,pcm", "data aggregation,privacy", "data controller", >> >> "data protection,encryption", "data protection,recovery", "data >> protection,security", >> >> "data quality,security", "data security,encryption,security", >> >> "data security,mac,security", "data security,personal data,security", >> >> "data security,prevention,security", "detection", "detection,mac", >> >> "detection,password", "deterrence,prevention", "digital signature", >> >> "disclosure,password", "disclosure,private information", >> "disclosure,security", >> >> "encryption,password,recovery", "encryption,private data", "id >> management,privacy", >> >> "id management,security", "identifier", "identifier,token", "location >> privacy,privacy", >> >> "mac,password,security", "mac,permission", "mac,prevention", >> >> "mac,privacy", "mac,pseudonym", "malicious,prevention", >> "non-repudiation", >> >> "password,prevention,security", "password,private information", >> >> "password,recovery", "password,user id", "permission,personal data", >> >> "permission,privacy,privacy policy", "personal data", "personal >> identification number,pin", >> >> "personal information", "personal information,security", "prevention", >> >> "prevention,privilege", "privacy,privacy policy", "privacy,privacy >> preferences", >> >> "private information,security", "recovery,retention", "recovery,token", >> >> "retention,token", "sensitive data", "token"), class = "factor")), >> .Names >> = c("class.1", >> >> "class.2", "class.3", "terms"), row.names = c(NA, 100L), class = >> "data.frame") >> >> On Mon, May 25, 2015 at 2:04 PM, John Kane <jrkrid...@inbox.com> wrote: >> >> Hi Mohammad, >> >> If you are just starting with R a sense of total confusion is often the >> first feeling. Welcome :). >> >> If you are a SAS or SPSS user this may help >> https://science.nature.nps.gov/im/datamgmt/statistics/r/documents/r_for_sas_spss_users.pdf >> [ >> https://science.nature.nps.gov/im/datamgmt/statistics/r/documents/r_for_sas_spss_users.pdf >> ] >> >> If anything, I am even more lost than before. >> >> Did Jim Lemon's approach help? Confuse ? >> >> Perhaps one of the problems is that the data did not come through >> cleanly. You posted in HTML and the R-help list strips out all HTML so >> the >> result often is mangled beyond any real use. >> >> I may have imagined that your data are more complicated than they >> really >> are if all you really want is some kind of frequency count possibly by >> some >> conditioning variable. Is this it? >> >> It seems too simple but that is what I read that Excel is doing (as >> incompetently as usual---I had not realised it was possible to be even >> less >> impressed with Excel than I already was.) >> >> Can you send us some more data in dput() format. See the links I >> provided >> earlier or have a look at ?dput for more information. >> >> If you have lot of data, a representative sample is fine. It is often >> enough to do something like : >> dput(head(mydata, 100)) >> which supplies 100 rows of data. >> >> Just output the dput() data, copy and paste into your email, et voilĂ >> we have the exact same data. >> >> The reason for dput() is that it provides a snapshot of exactly how the >> data exists on your machine. Given all sorts of differences between >> OS's, >> personal settings, human languages and so on. what I or another R-help >> reader see or read in may not correspond to what you have. Using dput() >> avoids all of this. >> >> Here is a simple example of what I mean. If you look at dat1 and dat2 >> they 'look' the same but ... I could read in data either way depending >> on >> all sorts of variable and have no idea which, if either is how you see >> the >> data. >> >> Data are supplied in dput() format, just copy and paste into R. >> ===== >> dat1 <- structure(list(aa = structure(1:10, .Label = c("1", "2", "3", >> "4", "5", "6", "7", "8", "9", "10"), class = "factor"), bb = c(10L, >> 9L, 8L, 7L, 6L, 5L, 4L, 3L, 2L, 1L)), .Names = c("aa", "bb"), row.names >> = >> c(NA, >> -10L), class = "data.frame") >> >> dat2 <- structure(list(aa = 1:10, bb = c(10L, 9L, 8L, 7L, 6L, 5L, 4L, >> 3L, 2L, 1L)), .Names = c("aa", "bb"), row.names = c(NA, -10L), class = >> "data.frame") >> >> dat1 >> dat2 # looks a lot like dat1 >> >> with(dat1, aa*bb) >> with(dat2 , aa*bb) >> >> str(dat1) >> str(dat2) >> >> ======= >> >> John Kane >> Kingston ON Canada >> >> -----Original Message----- >> From: mxalimoha...@ualr.edu >> Sent: Mon, 25 May 2015 12:14:46 -0500 >> To: jrkrid...@inbox.com >> Subject: Re: [R] Problem with comparing multiple data sets >> >> Hi John. >> >> Thank you for your response. >> >> Here is a small portion of my actual data set. What I am supposed to do >> is to use a function similar to mode function in excel to find the most >> frequent value (class) for each term. >> >> V1 V2 V3 V4 >> >> 1 class 1 class 2 class 3 terms >> >> 2 0 2 0 #dac >> >> 3 0 2 0 #dac >> >> 4 0 2 0 #dac >> >> 5 0 2 0 #dac >> >> 6 1 0 1 #dac >> >> 7 0 0 0 #dac >> >> .... >> >> Since I just started using R. I don't know where I am going with this. >> I >> appreciate any help. >> >> On Sat, May 23, 2015 at 8:23 AM, John Kane <jrkrid...@inbox.com> wrote: >> >> Hi Mohammad >> >> Welcome to the R-help list. >> >> There probably is a fairly easy way to what you want but I think we >> probably need a bit more background information on what you are trying >> to >> achieve. I know I'm not exactly clear on your decision rule(s). >> >> It would also be very useful to see some actual sample data in useable >> R >> format.Have a look at these links >> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example >> [ >> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example] >> [ >> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example >> [ >> http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example]] >> and http://adv-r.had.co.nz/Reproducibility.html [ >> http://adv-r.had.co.nz/Reproducibility.html] [ >> http://adv-r.had.co.nz/Reproducibility.html [ >> http://adv-r.had.co.nz/Reproducibility.html]] for some hints on what you >> might want to include in your question. >> >> In particular, read up about dput() in those links and/or see ?dput. >> This is the generally preferred way to supply sample or illustrative >> data >> to the R-help list. It basically creates a perfect copy of the data as >> it >> exists on 'your' machine so that R-help readers see exactly what you do. >> >> John Kane >> Kingston ON Canada >> >> > -----Original Message----- >> > From: mxalimoha...@ualr.edu >> > Sent: Fri, 22 May 2015 12:37:50 -0500 >> > To: r-help@r-project.org >> > Subject: [R] Problem with comparing multiple data sets >> > >> > Hi everyone, >> > >> > I am very new to R and I have a task to do. I appreciate any help. I >> have >> > 3 >> > data sets. Each data set has 4 columns. For example: >> > >> > Class Comment Term Text >> > 0 com1 aac text1 >> > 2 com2 aax text2 >> > 1 com3 vvx text3 >> > >> > Now I need t compare the class section between 3 data sets and >> assign >> the >> > most available class to that text. For example if text1 is assigned >> to >> > class 0 in data set 1&2 but assigned as 2 in data set 3 then it >> should >> be >> > assigned to class 0. If they are all the same so the class will be >> the >> > same. The ideal thing would be to keep the same format and just >> update >> > the >> > class. Is there any easy way to do this? >> > >> > Thanks a lot. >> > >> >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see >> >> > https://stat.ethz.ch/mailman/listinfo/r-help [ >> https://stat.ethz.ch/mailman/listinfo/r-help] [ >> https://stat.ethz.ch/mailman/listinfo/r-help [ >> https://stat.ethz.ch/mailman/listinfo/r-help]] >> > PLEASE do read the posting guide >> > http://www.R-project.org/posting-guide.html [ >> http://www.R-project.org/posting-guide.html] [ >> http://www.R-project.org/posting-guide.html [ >> http://www.R-project.org/posting-guide.html]] >> > and provide commented, minimal, self-contained, reproducible code. >> >> ____________________________________________________________ >> FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop! >> Check it out at http://www.inbox.com/earth >> [http://www.inbox.com/earth] >> [http://www.inbox.com/earth [http://www.inbox.com/earth]] >> >> -- >> >> Mohammad Alimohammadi | Graduate Assistant >> University of Arkansas at Little Rock | College of Science >> and Mathematics (CSAM) >> >> 501.346.8007 | mxalimoha...@ualr.edu | ualr.edu [http://ualr.edu] [ >> http://ualr.edu/ [http://ualr.edu/]] >> >> Public URL: http://scholar.google.com/citations?user=MsfN_i8AAAAJ [ >> http://scholar.google.com/citations?user=MsfN_i8AAAAJ] [ >> http://scholar.google.com/citations?user=MsfN_i8AAAAJ [ >> http://scholar.google.com/citations?user=MsfN_i8AAAAJ]] >> >> ____________________________________________________________ >> FREE ONLINE PHOTOSHARING - Share your photos online with your friends >> and >> family! >> Visit http://www.inbox.com/photosharing [ >> http://www.inbox.com/photosharing] to find out more! >> >> -- >> >> Mohammad Alimohammadi | Graduate Assistant >> University of Arkansas at Little Rock | College of Science and >> Mathematics >> (CSAM) >> >> 501.346.8007 | mxalimoha...@ualr.edu | ualr.edu [http://ualr.edu/] >> >> Public URL: http://scholar.google.com/citations?user=MsfN_i8AAAAJ [ >> http://scholar.google.com/citations?user=MsfN_i8AAAAJ] >> >> ____________________________________________________________ >> FREE 3D EARTH SCREENSAVER - Watch the Earth right on your desktop! >> Check it out at http://www.inbox.com/earth >> >> >> > > > -- > Mohammad Alimohammadi | Graduate Assistant > University of Arkansas at Little Rock | College of Science and > Mathematics > (CSAM) > 501.346.8007 | mxalimoha...@ualr.edu | ualr.edu > > Public URL: http://scholar.google.com/citations?user=MsfN_i8AAAAJ > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@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. ____________________________________________________________ Share photos & screenshots in seconds... 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