[R] Problem with comparing multiple data sets

Mohammad Alimohammadi mxalimohamma at ualr.edu
Wed May 27 16:18:12 CEST 2015


Hi John,

I created the original data set with dput . This time I only loaded 50
values for each data set (dat1, dat2, dat3).

About your question, all 0,1 and 2 are indicator of a specific class. The
task is to compare 3 independent classification of a certain term and and
determine the actual class of the term by finding the most frequent
assigned number for that term.

I thought it might be easier to combine them into 1 data frame but either
way is fine.

Let me know if it shows up clean. I saved the dput in txt file and copied
here from that file. I assume this is the right way to do it. I might be
wrong.


==============================================

*dat1*

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), terms = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 2L, 2L, 2L), .Label =
c("#dac",
"#mac,#security", "accountability,anonymous", "data
security,encryption,security"
), class = "factor")), .Names = c("class.1", "terms"), class =
"data.frame", row.names = c(NA,
-49L))


*dat2*

structure(list(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), terms = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 2L, 2L, 2L), .Label =
c("#dac",
"#mac,#security", "accountability,anonymous", "data
security,encryption,security"
), class = "factor")), .Names = c("class.2", "terms"), class =
"data.frame", row.names = c(NA,
-49L))

*dat3*

structure(list(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), terms = structure(c(1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 4L, 4L, 4L, 4L, 4L, 3L, 3L, 3L, 3L, 2L, 2L, 2L), .Label =
c("#dac",
"#mac,#security", "accountability,anonymous", "data
security,encryption,security"
), class = "factor")), .Names = c("class.3", "terms"), class =
"data.frame", row.names = c(NA,
-49L))

=============================================









On Wed, May 27, 2015 at 8:05 AM, John Kane <jrkrideau at inbox.com> wrote:

> Hi Mohammad,
>
> I went back and reread your original statement of the problem about and I
> think I kinda grasp it. It is actually quite clear and I misunderstood it
> completely.
>
> At the moment I have no idea how to approach it.  As Jim Lemon said, it
> looks easy but may not be.  I'll go back and re-examine Jim's approach.
>
> You might want to create three sample data sets of the original data
> layouts and upload them, in dput() format, to the list.  It may be easier
> to tackle from that approach.
>
> In any case, in the existing data set is a 2 a numeric value 2 or just an
> on/off indicator?
>
> John Kane
> Kingston ON Canada
>
>
> > -----Original Message-----
> > From: mxalimohamma at ualr.edu
> > Sent: Tue, 26 May 2015 20:11:08 -0500
> > To: r-help at 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 <jrkrideau at 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: mxalimohamma at ualr.edu
> >> Sent: Tue, 26 May 2015 09:50:43 -0500
> >> To: jrkrideau at 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 <jrkrideau at 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 voilà
> >> 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: mxalimohamma at ualr.edu
> >>  Sent: Mon, 25 May 2015 12:14:46 -0500
> >>  To: jrkrideau at 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 <jrkrideau at 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: mxalimohamma at ualr.edu
> >>   > Sent: Fri, 22 May 2015 12:37:50 -0500
> >>   > To: r-help at 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 at 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 | mxalimohamma at 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 | mxalimohamma at 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 | mxalimohamma at ualr.edu | ualr.edu
> >
> > Public URL: http://scholar.google.com/citations?user=MsfN_i8AAAAJ
> >
> >       [[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.
>
> ____________________________________________________________
> Can't remember your password? Do you need a strong and secure password?
> Use Password manager! It stores your passwords & protects your account.
> Check it out at http://mysecurelogon.com/password-manager
>
>
>


-- 
Mohammad Alimohammadi | Graduate Assistant
University of Arkansas at Little Rock | College of Science and Mathematics
(CSAM)
501.346.8007 | mxalimohamma at ualr.edu | ualr.edu

Public URL: http://scholar.google.com/citations?user=MsfN_i8AAAAJ

	[[alternative HTML version deleted]]



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