Python 在 Pandas 中从多索引恢复到单索引数据帧
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时间：2020-08-19 12:30:42 来源:igfitidea点击:
Reverting from multiindex to single index dataframe in pandas
提问by user308827
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
In the dataframe above, I have a multilevel index consisting of the columns:
在上面的数据框中，我有一个由列组成的多级索引：
names=[u'YEAR', u'MONTH', u'datetime']
How do I revert to a dataframe with 'datetime' as index and 'YEAR' and 'MONTH' as normal columns?
如何恢复到以“datetime”为索引、以“YEAR”和“MONTH”为普通列的数据框？
采纳答案by EdChum
pass level=[0,1]to just reset those levels:
通过level=[0,1]以重置这些级别：
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
you can pass the label names alternatively:
您也可以传递标签名称：
df.reset_index(level=['YEAR','MONTH'])
