Question

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我到目前为止，EdChum提供了以下代码：

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

这也很有效，但只要我更改dateframe = df的索引如下：

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)

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')

这是什么问题？我如何调整代码以使其与da DatetimeIndex一起使用？

Answer 1

以下工作，不同之处在于我使用get_loc获取索引中datetime值的整数位置：

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

Answer 2

仅仅是一个FYI，我通过将熊猫更新到最新的稳定版本来解决这个问题。

Python DatetimeIndex错误 - TypeError :(＆＃34;无法对<class'进行标签索引pandas.tseries.index.datetimeindex'=“”

2 个答案: