[R] Counting things

[Gabor Grothendieck]

Try this using built in data frame iris:

> length(subset(iris, Sepal.Length >= 7, Sepal.Width)[[1]])
[1] 13
> length(subset(iris, Sepal.Length >= 7 & Species == 'virginica', Sepal.Width)[[1]])
[1] 12

> # or the following (note that dot in Sepal.Length is automatically
> # converted to _ because dot has special meaning in sql)

> library(sqldf)
> sqldf("select count(*) from iris where Sepal_Length >= 7")
  count(*)
1       13
> sqldf("select count(*) from iris where Sepal_Length >= 7 and Species = 'virginica'")
  count(*)
1       12

For the second part use cut to create a factor with the levels you
want

 iris$Sepal.Length.factor <- cut(iris$Sepal.Length, 4:8)

and then summarize as desired using sql such as:

> sqldf("select Sepal_Length_factor, avg(Sepal_Length), count(Sepal_Length) from iris group by Sepal_Length_factor")
  Sepal_Length_factor avg(Sepal_Length) count(Sepal_Length)
1               (4,5]          4.787500                  32
2               (5,6]          5.550877                  57
3               (6,7]          6.473469                  49
4               (7,8]          7.475000                  12

or use summaryBy the in the doBy package.

See ?cut, ?subset, and in doBy see ?summaryBy  Also see
http://sqldf.googlecode.com

On Tue, Aug 4, 2009 at 11:40 PM, Noah Silverman<noah at smartmediacorp.com> wrote:
> I've completed an experiment and want to summarize the results.
>
> There are two things I like to create.
>
> 1) A simple count of things from the data.frame with predictions
>    1a) Number of predictions with probability greater than x
>    1b) Number of predictions with probability greater than x that are really
> true
>
>    In SQL, this would be,
>        "Select count(predictions) from data.frame where probability > x"
> "Select count(predictions) from data.frame where probability > x and label
> ='T' "
>
> How can I do this one in R?
>
>
> 2) I'd like to create what we call "binning".  It is a simple list of
> probability ranges and how accurate our model is.  The idea is to see how
> "true" our probabilities are.
> for example
>
> range        number of items        mean(probability)   true_accuracy
> 100-90%        20                            .924                    .90
> 90-80%          50                            .825                    .84
> 80-70%          214                          .75                      .71
> etc...
>
> It would be really great if I could also graph this!
>
> Is there any kind of package or way to do this in R
>
> Thanks!
>
> -N
>
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