[R] Mailinglist

Rui Barradas ruipb@rr@d@@ @ending from @@po@pt
Sun Jan 6 18:27:18 CET 2019 

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 <jdnewmil using 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 <drjimlemon using 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.thompson using 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 <drjimlemon using 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.thompson using 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 using 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 using 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 using 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.
>>
>

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