Python 透视表的反求
我有一个数据帧(例如,Python 透视表的反求,python,pandas,Python,Pandas,我有一个数据帧(例如,df_p),它已经转换成一个透视表: import pandas as pd df = pd.DataFrame({'start_year':[2000, 2001, 2002], 'end_year':[2010, 2011, 2012], 'price':[1.0, 2.0, 3.0]}) # end_year price start_year # 0 2010 1.0
df_p
),它已经转换成一个透视表:
import pandas as pd
df = pd.DataFrame({'start_year':[2000, 2001, 2002],
'end_year':[2010, 2011, 2012],
'price':[1.0, 2.0, 3.0]})
# end_year price start_year
# 0 2010 1.0 2000
# 1 2011 2.0 2001
# 2 2012 3.0 2002
df_p = df.pivot('start_year', 'end_year', 'price')
# end_year 2010 2011 2012
# start_year
# 2000 1.0 NaN NaN
# 2001 NaN 2.0 NaN
# 2002 NaN NaN 3.0
如何将df\u p
转换回df
?stack
melt
+dropna
(但不能保证在任何情况下都能正常工作)
你想保留
NaN
条目吗?@PatrickO'Connor不,我不想要
df_p.stack().reset_index(name='price')
start_year end_year price
0 2000 2010 1.0
1 2001 2011 2.0
2 2002 2012 3.0
df_p.reset_index().melt('start_year', value_name='price').dropna()
start_year end_year price
0 2000 2010 1.0
4 2001 2011 2.0
8 2002 2012 3.0