python - pandas argsort 的有趣结果

Question

我想我发现了 pandas 中的一个错误。我希望得到一些帮助来验证错误或帮助我找出我的代码中逻辑错误的位置。

我的代码如下:

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 > 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 > 0 else 29
fix_month = lambda x: x if x > 0 else 02
fix_year = lambda x: x if x > 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)

当我运行代码时，大部分结果都是正确的。以索引 6 为例:

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

但是，某些索引似乎会引发 pandas.argsort() 循环。以索引 10 为例:

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

argsort 应该返回 nan,1.0,2.0,0.0 而不是 nan,2.0,0.0,1.0。

我已经研究了三天了。在这一点上，我不确定是我还是错误。我不确定如何回溯它以获得答案。任何帮助将不胜感激!

Answer 1

您可能错误地解释了 argsort 的结果。 argsort 不给出值的排名。使用 rank方法，如果你想对值进行排名。

argsort 返回的 Series 中的值给出了丢弃 NaN 后原始值的相应位置。在您的例子中，由于您将 20200229 转换为 NaN，因此您正在对 NaN, 20080227, 20080410, 20080213 进行 argsorting。非 NaN 值是

nonnan = [20080227, 20080410, 20080213]

结果 NaN, 2, 0, 1 说:

argsort     sorted values
  NaN       NaN
   2        nonnan[2] = 20080213
   0        nonnan[0] = 20080227
   1        nonnan[1] = 20080410

所以我觉得还可以。