在Pandas中从多索引转换为单索引数据框 [英] Reverting from multiindex to single index dataframe in pandas

问题描述

                       NI
YEAR MONTH datetime        
2000 1     2000-01-01   NaN
           2000-01-02   NaN
           2000-01-03   NaN
           2000-01-04   NaN
           2000-01-05   NaN

在上面的数据框中，我有一个由列组成的多级索引:

In the dataframe above, I have a multilevel index consisting of the columns:

names=[u'YEAR', u'MONTH', u'datetime']

如何还原为以"datetime"作为索引并且以"YEAR"和"MONTH"作为普通列的数据框?

How do I revert to a dataframe with 'datetime' as index and 'YEAR' and 'MONTH' as normal columns?

推荐答案

通过level=[0,1]仅重置这些级别:

dist_df = dist_df.reset_index(level=[0,1])

In [28]:
df.reset_index(level=[0,1])

Out[28]:
            YEAR  MONTH  NI
datetime                     
2000-01-01  2000      1   NaN
2000-01-02  2000      1   NaN
2000-01-03  2000      1   NaN
2000-01-04  2000      1   NaN
2000-01-05  2000      1   NaN

您也可以传递标签名称:

you can pass the label names alternatively:

df.reset_index(level=['YEAR','MONTH'])

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