Hi Rui, Thank you, I willl look into it.
Best, Rachel On Sun, Jan 6, 2019 at 12:27 PM Rui Barradas <ruipbarra...@sapo.pt> wrote: > Hello, > > In many continental European countries, such as mine, the function to > use is > > read.csv2 > > It defaults to > > sep = ";", dec = "," > > Note that these functions are in fact calls to read.table with special > default arguments. Another default that changes is header = TRUE. > You might also want to set stringsAsFactors = FALSE since the default > value TRUE is a common source for errors. > > Hope this helps, > > Rui Barradas > > Às 16:45 de 06/01/2019, Michael Dewey escreveu: > > Dear Rachel > > > > Not sure if this is going to help but if it is a csv file then > > read.csv() is your friend. Read the help first in case you need to > > specify what is being used for the decimal point and the separator as if > > it is from the Netherlands they may not be the default settings. > > > > michael > > > > On 06/01/2019 16:37, Rachel Thompson wrote: > >> Hi Jeff, > >> > >> Thanks for your email. > >> I am an intern from Amsterdam and I have to do an analysis in R. I > >> spoke to > >> my professor in Amsterdam and my supervisor's here in Boston. But they > >> are > >> to busy to help. I informed them from the start that I am not familiar > >> with > >> R(Rstudio) and they told me that I would receive guidance. So since they > >> can not help me, I decided to share my problem online. > >> (It is a CVS file imported into R) > >> > >> Please understand that I am new to this. I will unsubscribe to the > >> mailing > >> list if my question does not belong here. > >> > >> Thanks, > >> > >> Rachel > >> > >> On Sun, Jan 6, 2019 at 11:01 AM Jeff Newmiller < > jdnew...@dcn.davis.ca.us> > >> wrote: > >> > >>> I would not want to leave the impression that I think the task at > >>> hand is > >>> merely tedious... my point is that there are numerous steps involved > and > >>> each step depends on information that has not been communicated to the > >>> list, and there is a learning curve even in knowing what to include > >>> in an > >>> email question. What I do think is that knowing enough basic R syntax > to > >>> express small bits of the problem in R will be a vast improvement over > >>> attempting to use only English descriptions, and Rachel has to bridge > >>> that > >>> initial gap. > >>> > >>> For example, some images of data were apparently sent to Jim only, > >>> yet he > >>> still does not know in what format the data file is stored, so that > >>> technique was not very effective. One way for the question to become > >>> more > >>> focused is for Rachel to study up on her own how to import data and > >>> provide > >>> us with a "dput" (see the StackOverflow discussion I referenced > >>> before) of > >>> a small sample of data. Another is for Rachel to use basic R syntax to > >>> create an anonymous data set from scratch (also outlined in the SO > >>> discussion). These approaches allow us to keep the focus of our mailing > >>> list discussion on manipulating the data into summaries. Another > >>> approach > >>> is to re-focus the question on importing data by supplying a download > >>> link > >>> to the data so we can make suggestions as to what R commands will > handle > >>> this data in its raw form. In any case, we cannot leapfrog over the > >>> data to > >>> the analysis as the question stands. > >>> > >>> Given the above, I have to wonder why Rachel hasn't simply used the > tool > >>> she is familiar with... SPSS... to do this? If it is because this is an > >>> academic assignment to learn R then she should be talking to her > >>> institutional support (instructor/teaching assistant/tutoring staff) > >>> anyway > >>> since there is a no-homework policy on this list (and that avenue would > >>> have the benefit of being conducted orally and most likely in her > native > >>> language). > >>> > >>> > >>> On January 6, 2019 1:12:46 AM PST, Jim Lemon <drjimle...@gmail.com> > >>> wrote: > >>>> Hi Rachel, > >>>> It looks to me as though the first thing you want to do is to get your > >>>> data, which you attach as images, into a data frame. If these are flat > >>>> files like CSV or TAB, you should be able to read them in with some > >>>> variant of the read.table function. If Excel, look at the various > >>>> Excel import packages. Then you can operate on the data frame by doing > >>>> things like tabulating Participant ID against the code for SMS or call > >>>> (which I assume are those 3000+ numbers). You can take the differences > >>>> in what look like POSIX time values between successive TRUE and FALSE > >>>> screen values to get the duration of screen activity and it looks like > >>>> participant activity is recorded at regular intervals. As Jeff > >>>> suggested, this is really just boring work figuring out how to extract > >>>> the events: > >>>> > >>>> call_indices<-which(Probetype == xxxxxxCallLogProbe & ValueSpecified > >>>> == _id & Valuedetailed ==3271) > >>>> > >>>> using suitable logical statements and then tabulating them by > >>>> ParticipantID. If you know how to do that in SPSS, it won't be too > >>>> hard to translate the logical statements into R syntax as above. I may > >>>> have misunderstood the variable names, but I think the logic is clear. > >>>> > >>>> Jim > >>>> > >>>> On Sun, Jan 6, 2019 at 4:07 PM Rachel Thompson > >>>> <rachel.thomp...@student.uva.nl> wrote: > >>>>> > >>>>> Hi Jim, > >>>>> > >>>>> Thank you for the clarification. Since I only work in SPSS and I am > >>> >from Amsterdam I have had problems with specifying what I am trying to > >>>> do in this specific program and also in clear English language. > >>>>> > >>>>> I think I want to indeed aggregate these events for each subject over > >>>> the observation. But in this case several observations. > >>>>> 1. I want to have a summary of how many times a specific subject got > >>>> called (CallLogProbe) > >>>>> 2. I want to have a summary of how many times a specific subject got > >>>> a text message (SMS probe) > >>>>> 3. I want to have a summary of how many times a specific subject > >>>>> - Turned their screen on - True (ScreenProbe) > >>>>> - Or did not turn their screen on - False (ScreenProbe) > >>>>> 4. I want to have a summary of the activity level of a specific > >>>> subject > >>>>> - Activity level - none (ActivityProbe) > >>>>> - Activity level- low (ActivityProbe) > >>>>> - Activity level - High (ActivityProbe) > >>>>> > >>>>> I want to do this for all the 36 subjects(Participants). > >>>>> > >>>>> In the end, I have to define percentages, so I am able to > >>>> say...Subject 36 has low social interactions ( because they only got > >>>> called and texted 500 times in total, while the average of all the > >>>> participants is 10000 or something). I have to come up with the > >>>> percentages myself and define cutoff points of what is considered > >>>> low-medium-high, based on what the results of all the subjects are. > >>>>> > >>>>> I hope that I am as clear as possible . > >>>>> > >>>>> > >>>>> I feel as if I am on my way of understanding it, but since I do not > >>>> clearly know, I am trying out a lot of different codes etc. and I do > >>>> not know if I am doing the right thing. I indeed made a new data frame > >>>> etc, but I still feel a bit lost. Do I need to make one per subject or > >>>> per Probe etc.. > >>>>> > >>>>> > >>>>> Thanks for your help. I hope that you can help me resolve this issue. > >>>>> > >>>>> > >>>>> Best, > >>>>> > >>>>> > >>>>> Rachel > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> > >>>>> On Sat, Jan 5, 2019 at 9:03 PM Jim Lemon <drjimle...@gmail.com> > >>>> wrote: > >>>>>> > >>>>>> Hi Rachel, > >>>>>> I'll take a guess and assume that you are monitoring the mobile > >>>> phones > >>>>>> of 36 people, adding an observation every time some specified change > >>>>>> of state is sensed on each device. I'll also assume that you are > >>>> only > >>>>>> recording four types of measurement. It seems that you want to > >>>>>> aggregate these events for each subject over the interval or > >>>>>> observation (or over each day or something). I think you are going > >>>> to > >>>>>> create a new data frame of these summaries from the one you have of > >>>>>> individual observations. Creating each summary doesn't look too > >>>> hard, > >>>>>> but you will have to define more precisely what you want those > >>>>>> summaries to be. For instance, "I want the mean activity level for > >>>>>> each subject during the overall time that their mobile phone is > >>>>>> switched on", One you have clearly defined your goals, it probably > >>>>>> won't be too hard to get to them. > >>>>>> > >>>>>> Jim > >>>>>> > >>>>>> On Sun, Jan 6, 2019 at 5:39 AM Rachel Thompson > >>>>>> <rachel.thomp...@student.uva.nl> wrote: > >>>>>>> > >>>>>>> Dear Mr/Mrs, > >>>>>>> > >>>>>>> This is my first time working in R studio. > >>>>>>> I have a database of 36 participants but it has 150600 entries. > >>>>>>> Column - Column - Column - Column > >>>>>>> > >>>>>>> Participant Activityprobe - Activity Level - High/low/none > >>>>>>> > >>>>>>> Participant Screenprobe - screenon/off - > >>>>>>> > >>>>>>> Participant SMSprobe etc > >>>>>>> > >>>>>>> Participant CallLogProbe etc. > >>>>>>> > >>>>>>> I need a code that helps me count the activity level of all the > >>>> participants > >>>>>>> High activity level. No activity level and Low activity level. > >>>>>>> And to help me find out for every participant what the percentages > >>>> are of > >>>>>>> all their high/no/low activity. > >>>>>>> > >>>>>>> For screenprobe I need to count how many times the participant > >>>> turned their > >>>>>>> screen on and how many times they turned it off and the percentage > >>>> of > >>>>>>> screen on/off. > >>>>>>> > >>>>>>> For callLog I need to count how many times each participant got > >>>> called and > >>>>>>> the percentage. > >>>>>>> > >>>>>>> For SMS I need to count the number of SMS for each participant and > >>>> their > >>>>>>> percentage. > >>>>>>> > >>>>>>> I also need to categorize the probes. So that my database shows > >>>> all the > >>>>>>> activity levels first, organized by none/high/low and then all the > >>>>>>> screenprobes, organized by on and off etc... > >>>>>>> > >>>>>>> I hope that my description is clear and that you can maybe help > >>>> me. > >>>>>>> > >>>>>>> Best, > >>>>>>> > >>>>>>> Rachel > >>>>>>> > >>>>>>> [[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. > >>>> > >>>> ______________________________________________ > >>>> 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. > >>> > >>> -- > >>> Sent from my phone. Please excuse my brevity. > >>> > >> > >> [[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. > >> > > > [[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.
