A few more came to mind:

VIM package (for exploring missing data):
http://cran.r-project.org/web/packages/VIM/index.html
http://bm2.genes.nig.ac.jp/RGM2/index.php?scope=name&query=VIM

And the basic commands:
* edit (for seeing the dataframe as in a spreadsheet)
And the commands:
* head   (and)   tail


Tal




----------------Contact
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Contact me: Tal.Galili@gmail.com |  972-52-7275845
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On Sun, Nov 22, 2009 at 3:15 PM, Tal Galili <tal.galili@gmail.com> wrote:

> Here is one more function for the list:
> "whatis"
> from the package:
> "YaleToolkit"
> See:
> http://cran.r-project.org/web/packages/YaleToolkit/
>
>
>
> I also like using:
> ls()
> ls.str()
> And sometimes (for just one variable):
> stem (which can be viewd as an ascii histogram)
>
>
> Wonderful question and list, I hope for more answers.
>
>
> Tal
>
> ----------------Contact
> Details:-------------------------------------------------------
> Contact me: Tal.Galili@gmail.com |  972-52-7275845
> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) |
> www.r-statistics.com/ (English)
>
> ----------------------------------------------------------------------------------------------
>
>
>
>
>
> On Sun, Nov 22, 2009 at 12:01 AM, frenchcr <frenchcr@btinternet.com>wrote:
>
>>
>> i just found the following list, i wondered if anybody could add to this
>> as i
>> have to characterize a large data set and am new to R...the list below was
>> so helpful....can you add to this???
>>
>> Just to forestall confusion amongst those who would like to use one of
>> the functions called "describe"...
>>
>> Hmisc package - describe
>> numeric
>>  name
>>  count of observations
>>  count of missing values
>>  count of unique values
>>  mean
>>  seven quantiles
>>  five lowest and highest values
>> discrete (factor or numeric with <= 10 unique values) -
>>  as for numeric, but
>>  no mean, quantiles or low/high values and
>>  including a frequency/percent display for each value.
>>
>> psych package - describe
>>  item name
>>  item number
>>  number of valid cases
>>  mean
>>  standard deviation
>>  median
>>  mad: median absolute deviation (from the median)
>>  minimum
>>  maximum
>>  skew (optional)
>>  kurtosis (optional)
>>  standard error
>>
>> prettyR package - describe
>> numeric
>>  name
>>  mean
>>  median
>>  var
>>  sd
>>  valid.n
>> the above are the defaults - the user can specify the name(s) of any
>> function(s) as an argument to the function to customize the display.
>> factor
>>  name
>>  count for each value
>>  percent for each value
>>  modal value
>>  count of missing values
>> logical
>>  name
>>  count of FALSE
>>  count of TRUE
>>  percent of TRUE
>>  count of missing values
>>
>>
>>
>> ....are there any more packages that help decribe and explore data sets
>> ????
>> --
>> View this message in context:
>> http://old.nabble.com/other-decriptive-stats-packages-tp26460757p26460757.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> 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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