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[英]Combine MultiIndex columns to a single index in a pandas dataframe
[英]Reverting from multiindex to single index dataframe in pandas
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
在上面的數據框中,我有一個由列組成的多級索引:
names=[u'YEAR', u'MONTH', u'datetime']
如何恢復到以“datetime”為索引、以“YEAR”和“MONTH”為普通列的數據框?
通過level=[0,1]
來重置這些級別:
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
您也可以傳遞標簽名稱:
df.reset_index(level=['YEAR','MONTH'])
另一種簡單的方法是為數據框設置列
consolidated_data.columns=country_master
參考: https : //riptutorial.com/pandas/example/18695/how-to-change-multiindex-columns-to-standard-columns
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