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[Octave-bug-tracker] [bug #32168] [octave forge] (dataframe) skewness, k


From: Nicholas Jankowski
Subject: [Octave-bug-tracker] [bug #32168] [octave forge] (dataframe) skewness, kurtosis not properly handling data with stdev=0
Date: Thu, 8 Dec 2022 15:56:31 -0500 (EST)

Update of bug #32168 (project octave):

                  Status:                    None => Confirmed              
        Operating System:               GNU/Linux => Any                    
                 Summary: [octave forge] (dataframe) support for skewness,
kurtosis => [octave forge] (dataframe) skewness, kurtosis not properly
handling data with stdev=0

    _______________________________________________________

Follow-up Comment #12:

testing on octave 8.0.1 with dataframe 1.2.0:


>> x = dataframe(rand(5,1))
warning: genvarname is obsolete; use matlab.lang.makeValidName or matlab.lang
.makeUniqueStrings instead
x = dataframe with 5 rows and 1 columns
_1      X
Nr double
 1 0.9377
 2 0.8110
 3 0.9436
 4 0.9106
 5 0.1947

>> skewness (x.data)
ans = -1.4022

>> skewness (x)
ans = dataframe with 1 rows and 1 columns
_1       X
Nr  double
 1 -1.4022

>> kurtosis (x.data)
ans = 3.1050

>> kurtosis (x)
ans = dataframe with 1 rows and 1 columns
_1      X
Nr double
 1 3.1050

(all still good there for first report problem)


   嬂᪁>> x = dataframe (zeros (5, 1))
x = dataframe with 5 rows and 1 columns
_1      X
Nr double
 1      0
 2      0
 3      0
 4      0
 5      0
>> skewness (x.data)
ans = NaN
>> skewness (x)
error: x(1): out of bound 0 (dimensions are 0x0)
error: called from
    df_mapper>@<anonymous> at line 28 column 30
    df_mapper at line 28 column 15
    power at line 22 column 8
    skewness at line 122 column 10
>> kurtosis (x.data)
ans = NaN
>> kurtosis (x)
error: x(1): out of bound 0 (dimensions are 0x0)
error: called from
    df_mapper>@<anonymous> at line 28 column 30
    df_mapper at line 28 column 15
    power at line 22 column 8
    kurtosis at line 125 column 10


so status unchanged from comment #9.  retitling to focus on one remaining
issue, which was suggested in comment #2 should be handled better by
overloading the functions in the dataframe class.


    _______________________________________________________

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