尝试访问索引时出现 Python Pandas 键错误
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Python Pandas Key Error When Trying to Access Index
提问by Curious Student
I have the following data set of stocks along the columns, dates down the rows(downloaded using Bloomberg's Python API - please ignore fact that they are all 'NaN' - this is just for this portion of the data):
我在列中有以下股票数据集，日期在行中（使用彭博的 Python API 下载 - 请忽略它们都是 'NaN' 的事实 - 这仅适用于这部分数据）：
I am trying to extract the Month and Years from the Index in order to later do a pivot:
我试图从索引中提取月份和年份，以便以后进行数据透视：
values['month'] = values['date'].apply(lambda x: x.month)
Where values is the name of the above DataFrame.
其中 values 是上述 DataFrame 的名称。
However this gives an error: 'KeyError 'date'
然而，这给出了一个错误：'KeyError 'date'
Running:
跑步：
values.index
Looks fine:
看起来不错：
DatetimeIndex(['2010-01-01', '2010-01-02', '2010-01-03', '2010-01-23',
'2010-01-24', '2010-01-29', '2010-01-30', '2010-01-31',
'2010-02-13', '2010-02-14',
...
'2017-08-12', '2017-08-27', '2017-08-31', '2017-09-01',
'2017-09-03', '2017-09-09', '2017-09-24', '2017-09-29',
'2017-09-30', '2017-10-01'],
dtype='datetime64[ns]', name='date', length=593, freq=None)
So I am just wondering what is going wrong and why I don't seem able to access the actual index here?
所以我只是想知道出了什么问题，为什么我似乎无法在这里访问实际索引？
采纳答案by jezrael
First columns is called indexand dateis index.name.
第一列被调用index并且date是index.name。
You can check it by:
您可以通过以下方式检查：
print (df.index.name)
So you need DatetimeIndex.monthand DatetimeIndex.year:
所以你需要DatetimeIndex.month和DatetimeIndex.year：
values.index.month
EDIT:
编辑：
For custom string format dates are used as strftime:
对于自定义字符串格式，日期用作strftime：
values['name'] = values.index.strftime('%B - %Y')
