python把日期转换为时间索引_Python Pandas日期时间索引转换

我有一个字典包含两个numpy数组，一个在日期时间.日期时间另一个是一个隐藏的数据数组。我试着用datetime数组作为DatetimeIndex将其放入Pandas中，但我失败了。在In [62]: dict1

Out[62]:

{'filltimes': array([datetime.datetime(2013, 8, 12, 12, 0, 1),

datetime.datetime(2013, 8, 12, 12, 30, 1),

datetime.datetime(2013, 8, 12, 13, 0, 1), ...,

datetime.datetime(2013, 9, 14, 19, 0, 1),

datetime.datetime(2013, 9, 14, 19, 30, 1),

datetime.datetime(2013, 9, 14, 20, 0, 1)], dtype=object),

'fillvals': masked_array(data = [5.553 2.604 2.604 ..., 16.896 17.271 18.022],

mask = [False False False ..., False False False],

fill_value = 1e+20)

}

In [63]: type(dict1)

Out[63]: dict

In [64]: type(dict1['filltimes'])

Out[64]: numpy.ndarray

In [65]: type(dict1['filltimes'][0])

Out[65]: datetime.datetime

In [66]: pd1=pd.DataFrame.from_dict(dict1)

In [67]: type(pd1)

Out[67]: pandas.core.frame.DataFrame

In [68]: type(pd1['filltimes'])

Out[68]: pandas.core.series.Series

In [69]: type(pd1['filltimes'][0])

Out[69]: pandas.tslib.Timestamp

In [70]: pd1.resample('D', how = 'mean')

---------------------------------------------------------------------------

TypeError Traceback (most recent call last)

in ()

----> 1 pd1.resample('D', how = 'mean')

/Users/andrew/anaconda/lib/python2.7/site-packages/pandas/core/generic.pyc in resample(self, rule, how, axis, fill_method, closed, label, convention, kind, loffset, limit, base)

2777 fill_method=fill_method, convention=convention,

2778 limit=limit, base=base)

-> 2779 return sampler.resample(self).__finalize__(self)

2780

2781 def first(self, offset):

/Users/andrew/anaconda/lib/python2.7/site-packages/pandas/tseries/resample.pyc in resample(self, obj)

99 return obj

100 else: # pragma: no cover

--> 101 raise TypeError('Only valid with DatetimeIndex or PeriodIndex')

102

103 rs_axis = rs._get_axis(self.axis)

TypeError: Only valid with DatetimeIndex or PeriodIndex

In [71]: pd1.reindex(pd.DatetimeIndex(pd.to_datetime(pd1['filltimes'])))

Out[71]:

filltimes fillvals

2013-08-12 12:00:01 NaT NaN

2013-08-12 12:30:01 NaT NaN

2013-08-12 13:00:01 NaT NaN

2013-08-12 13:30:01 NaT NaN

2013-08-12 14:00:01 NaT NaN

2013-08-12 14:30:01 NaT NaN

2013-08-12 15:00:01 NaT NaN

2013-08-12 15:30:01 NaT NaN

2013-08-12 16:00:01 NaT NaN

2013-08-12 16:30:01 NaT NaN

2013-08-12 17:00:01 NaT NaN

2013-08-12 17:30:01 NaT NaN

2013-08-12 18:00:01 NaT NaN

2013-08-12 18:30:01 NaT NaN

2013-08-12 19:00:01 NaT NaN

2013-08-12 19:30:01 NaT NaN

2013-08-12 20:00:01 NaT NaN

2013-08-12 20:30:01 NaT NaN

2013-08-12 21:00:01 NaT NaN

2013-08-12 21:30:01 NaT NaN

2013-08-12 22:00:01 NaT NaN

2013-08-12 22:30:01 NaT NaN

2013-08-12 23:00:01 NaT NaN

2013-08-12 23:30:01 NaT NaN

2013-08-13 00:00:01 NaT NaN

2013-08-13 00:30:01 NaT NaN

2013-08-13 01:00:01 NaT NaN

2013-08-13 01:30:01 NaT NaN

2013-08-13 02:00:01 NaT NaN

2013-08-13 02:30:01 NaT NaN

2013-08-13 03:00:01 NaT NaN

2013-08-13 03:30:01 NaT NaN

2013-08-13 04:00:01 NaT NaN

2013-08-13 04:30:01 NaT NaN

2013-08-13 05:00:01 NaT NaN

2013-08-13 05:30:01 NaT NaN

2013-08-13 06:00:01 NaT NaN

2013-08-13 06:30:01 NaT NaN

2013-08-13 07:00:01 NaT NaN

2013-08-13 07:30:01 NaT NaN

2013-08-13 08:00:01 NaT NaN

2013-08-13 08:30:01 NaT NaN

2013-08-13 09:00:01 NaT NaN

2013-08-13 09:30:01 NaT NaN

2013-08-13 10:00:01 NaT NaN

2013-08-13 10:30:01 NaT NaN

2013-08-13 11:00:01 NaT NaN

2013-08-13 11:30:01 NaT NaN

2013-08-13 12:00:01 NaT NaN

2013-08-13 12:30:01 NaT NaN

2013-08-13 13:00:01 NaT NaN

2013-08-13 13:30:01 NaT NaN

2013-08-13 14:00:01 NaT NaN

2013-08-13 14:30:01 NaT NaN

2013-08-13 15:00:01 NaT NaN

2013-08-13 15:30:01 NaT NaN

2013-08-13 16:00:01 NaT NaN

2013-08-13 16:30:01 NaT NaN

2013-08-13 17:00:01 NaT NaN

2013-08-13 17:30:01 NaT NaN

... ...

[1601 rows x 2 columns]

In [72]:

正如您所看到的，重新编制索引并没有产生我所期望的或者至少是我希望的结果。不仅丢失了所有数据，而且重新编制索引的操作也没有得到保留：

^{pr2}$

如果你能给我一两个指点，我会非常感激的。和熊猫在一起的整个约会/时间都快疯了。在