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POFunny results with pandas argsort
 

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  1. POFunny results with pandas argsort
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    <p>I think I have hit on a bug in pandas. I was hoping to get some help either verifying the bug or helping me figure out where my logic error is located in my code.</p> <p>My code is as follows:</p> <pre><code>import pandas, numpy, StringIO def sq_fixer(sr): sr = sr.where(sr != '20200229') ranks = sr.argsort().astype(float) ranks[ranks == -1] = numpy.nan return ','.join(ranks.astype(numpy.str)) def correct_date(sr): date_fixer = lambda x: pandas.datetime(x.year -100, x.month, x.day) if x &gt; pandas.datetime.now() else x sr = pandas.to_datetime(sr).apply(date_fixer).astype(pandas.datetime) return sr txt = '''ID,RUN_START_DATE,PUSHUP_START_DATE,SITUP_START_DATE,PULLUP_START_DATE 1,2013-01-24,2013-01-02,,2013-02-03 2,2013-01-30,2013-01-21,2013-01-13,2013-01-06 3,2013-01-29,2013-01-28,2013-01-01,2013-01-29 4,2013-02-16,2013-02-12,2013-01-04,2013-02-11 5,2013-01-06,2013-02-07,2013-02-25,2013-02-12 6,2013-01-26,2013-01-28,2013-02-12,2013-01-10 7,2013-01-26,,2013-01-12,2013-01-30 8,2013-01-03,2013-01-24,2013-01-19,2013-01-02 9,2013-01-22,2013-01-13,2013-02-03, 10,2013-02-06,2013-01-16,2013-02-07,2013-01-11 3347,,2008-02-27,2008-04-10,2008-02-13 3588,2004-09-12,,2004-11-06,2004-09-06 3784,2003-02-22,,2003-06-21,2003-02-19 593,2009-04-03,,2009-06-01,2009-04-01 4148,2003-03-21,2002-09-20,2003-04-01,2003-01-01 4299,2004-05-24,2004-07-23,,2004-04-22 4590,2005-05-05,2005-12-05,2005-04-05, 4830,2001-06-12,2000-10-12,2001-07-28,2001-01-28 4941,2006-11-08,2006-12-19,2006-07-19,2007-02-24 1416,2004-04-03,2004-05-19,2004-02-06, 1580,2008-12-20,,2009-03-19,2008-12-19 1661,2005-10-03,2005-10-26,2005-09-12,2006-02-19 1759,2001-10-18,,2002-01-17,2001-10-17 1858,2003-04-14,2003-05-17,,2002-12-17 1972,2003-06-01,2003-07-14,2002-12-14, 5905,2000-11-18,2001-01-13,,2000-11-04 2052,2002-06-11,,2002-08-23,2001-12-12 2165,2006-10-01,,2007-02-27,2006-09-30 2218,2007-09-19,,2008-02-06,2007-09-09 2350,2000-08-08,,2000-09-22,2000-01-08 2432,2001-08-22,,2001-09-25,2000-12-16 2611,2005-05-07,,2005-06-05,2005-03-26 2612,2005-05-06,,2005-05-26,2005-04-11 7378,2009-08-07,2009-01-30,2010-01-20,2009-06-08 7550,2006-04-08,,2006-06-01,2006-04-01 ''' df = pandas.read_csv(StringIO.StringIO(txt)) sequence_array = ['RUN_START_DATE', 'PUSHUP_START_DATE', 'SITUP_START_DATE', 'PULLUP_START_DATE'] xsequence_array = ['X_RUN_START_DATE', 'X_PUSHUP_START_DATE', 'X_SITUP_START_DATE', 'X_PULLUP_START_DATE'] df[sequence_array] = df[sequence_array].apply(correct_date, axis=1) fix_day = lambda x: x if x &gt; 0 else 29 fix_month = lambda x: x if x &gt; 0 else 02 fix_year = lambda x: x if x &gt; 0 else 2020 for col in sequence_array: xcol = 'X_{0}'.format(col) df[xcol] = ['{0:04d}{1:02d}{2:02d}'.format(fix_year(c.year), fix_month(c.month), fix_day(c.day)) for c in df[col]] df['X_AS_SEQUENCE'] = df[xsequence_array].apply(sq_fixer, axis=1) </code></pre> <p>When I run the code most of the results are correct. Take for example index 6:</p> <pre><code>In [31]: df.ix[6] Out[31]: ID 7 RUN_START_DATE 2013-01-26 00:00:00 PUSHUP_START_DATE NaN SITUP_START_DATE 2013-01-12 00:00:00 PULLUP_START_DATE 2013-01-30 00:00:00 X_RUN_START_DATE 20130126 X_PUSHUP_START_DATE 20200229 X_SITUP_START_DATE 20130112 X_PULLUP_START_DATE 20130130 X_AS_SEQUENCE 1.0,nan,0.0,2.0 </code></pre> <p>However, certain indices seem to throw pandas.argsort() for a loop. Take for example index 10:</p> <pre><code>In [32]: df.ix[10] Out[32]: ID 3347 RUN_START_DATE NaN PUSHUP_START_DATE 2008-02-27 00:00:00 SITUP_START_DATE 2008-04-10 00:00:00 PULLUP_START_DATE 2008-02-13 00:00:00 X_RUN_START_DATE 20200229 X_PUSHUP_START_DATE 20080227 X_SITUP_START_DATE 20080410 X_PULLUP_START_DATE 20080213 X_AS_SEQUENCE nan,2.0,0.0,1.0 </code></pre> <p>The argsort should return <code>nan,1.0,2.0,0.0</code> instead of <code>nan,2.0,0.0,1.0</code>.</p> <p>I have been on this for three days. At this point I am not sure if it is me or a bug. I am not sure how to backtrace it to get an answer. Any help would be most appreciated!</p>
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    1. COWhat version of pandas are you using? I'm using 0.11.0-dev and then get an error `AttributeError: 'float' object has no attribute 'year'` in Line 71
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      1. USwaitingkuo
    2. CO@waitingkuo There was a minor mistake in the code. I have put the correct code on pastebin. The long and the short of it was that I used pandas.datetime and not numpy.datetime64. http://pastebin.com/Fwbmsk5F
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