Python DatetimeIndex 错误 - TypeError: (“不能在 <class 'pandas.tseries.index.DatetimeIndex' 上做标签索引
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Python DatetimeIndex Error - TypeError: ("cannot do label indexing on <class 'pandas.tseries.index.DatetimeIndex'
提问by hb.klein
I have so far the following code provided by EdChum:
到目前为止，我有 EdChum 提供的以下代码：
In [1]:
df = pd.DataFrame({'a': [None] * 6, 'b': [2, 3, 10, 3, 5, 8]})
df["c"] =np.NaN
df["c"][0] = 1
df["c"][2] = 3
def func(x):
if pd.notnull(x['c']):
return x['c']
else:
return df.iloc[x.name - 1]['c'] * x['b']
df['c'] = df.apply(func, axis =1)
df['c'] = df.apply(func, axis =1)
df['c'] = df.apply(func, axis =1)
df
Out[1]:
a b c
0 None 2 1
1 None 3 3
2 None 10 3
3 None 3 9
4 None 5 45
5 None 8 360
That also works perfectly well, but as soon as I change the index of the dateframe = df as follows:
这也很有效，但是只要我按如下方式更改 dateframe = df 的索引：
rng = pd.date_range('1/1/2011', periods=6, freq='D')
df = pd.DataFrame({'a': [None] * 6, 'b': [2, 3, 10, 3, 5, 8]},index=rng)
I get the following error: TypeError: ("cannot do label indexing on <class 'pandas.tseries.index.DatetimeIndex'> with these indexers [2011-01-01 00:00:00] of <class 'pandas.tslib.Timestamp'>", u'occurred at index 2011-01-02 00:00:00')
我收到以下错误： TypeError: ("cannot do label indexing on <class 'pandas.tseries.index.DatetimeIndex'> with these indexers [2011-01-01 00:00:00] of <class 'pandas.tslib.Timestamp'>", u'occurred at index 2011-01-02 00:00:00')
What is the problem here? How do I need to adjust the code in order to make it work with da DatetimeIndex?
这里有什么问题？我需要如何调整代码才能使其与 da DatetimeIndex 一起使用？
回答by EdChum
The following works, the difference here is that I get the integer location of the datetime value in the index using get_loc:
以下工作，这里的区别在于我使用以下方法获取索引中日期时间值的整数位置get_loc：
In [48]:
rng = pd.date_range('1/1/2011', periods=6, freq='D')
df = pd.DataFrame({'a': [None] * 6, 'b': [2, 3, 10, 3, 5, 8]},index=rng)
df["c"] =np.NaN
?
df["c"][0] = 1
df["c"][2] = 3
?
?
def func(x):
if pd.notnull(x['c']):
return x['c']
else:
return df.iloc[df.index.get_loc(x.name) - 1]['c'] * x['b']
df['c'] = df.apply(func, axis =1)
df['c'] = df.apply(func, axis =1)
df['c'] = df.apply(func, axis =1)
df
Out[48]:
a b c
2011-01-01 None 2 1
2011-01-02 None 3 3
2011-01-03 None 10 3
2011-01-04 None 3 9
2011-01-05 None 5 45
2011-01-06 None 8 360
