Python 将虚拟列添加到原始数据帧
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原文地址: http://stackoverflow.com/questions/23208745/
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adding dummy columns to the original dataframe
提问by Brad
I have a dataframe looks like this:
我有一个数据框看起来像这样：
????????????JOINED_CO GENDER ???EXEC_FULLNAME ?GVKEY ?YEAR ?CONAME ?BECAMECEO ?REJOIN ??LEFTOFC ???LEFTCO ?RELEFT ???REASON ?PAGE CO_PER_ROL ???????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????? 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1992 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1993 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1994 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1995 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1996 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1997 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5622 ?????????????NaN ??MALE ??Ira A. Eichner ??1004 ?1998 ?AAR CORP ??19550101 ????NaN ?19961001 ?19990531 ????NaN ?RESIGNED ???79 5623 ?????????????NaN ??MALE ?David P. Storch ??1004 ?1992 ?AAR CORP ??19961009 ????NaN ??????NaN ??????NaN ????NaN ??????NaN ???57 5623 ?????????????NaN ??MALE ?David P. Storch ??1004 ?1993 ?AAR CORP ??19961009 ????NaN ??????NaN ??????NaN ????NaN ??????NaN ???57 5623 ?????????????NaN ??MALE ?David P. Storch ??1004 ?1994 ?AAR CORP ??19961009 ????NaN ??????NaN ??????NaN ????NaN ??????NaN ???57 5623 ?????????????NaN ??MALE ?David P. Storch ??1004 ?1995 ?AAR CORP ??19961009 ????NaN ??????NaN ??????NaN ????NaN ??????NaN ???57 5623 ?????????????NaN ??MALE ?David P. Storch ??1004 ?1996 ?AAR CORP ??19961009 ????NaN ??????NaN ??????NaN ????NaN ??????NaN ???57
For the YEAR value, I like to add year columns (1993,1994...,2009) to the original dataframe, If the value in YEAR is 1992, then the value in the 1992 column should be 1 otherwise 0.
对于 YEAR 值，我喜欢在原始数据框中添加年份列 (1993,1994...,2009)，如果 YEAR 中的值为 1992，则 1992 列中的值应为 1，否则为 0。
I used a very stupid for loop, but it seems to run forever as I have a large dataset. Could anyone help me with it, thanks a lot!
我使用了一个非常愚蠢的 for 循环，但它似乎永远运行，因为我有一个大数据集。谁能帮我解决一下，非常感谢！
采纳答案by unutbu
In [77]: df = pd.concat([df, pd.get_dummies(df['YEAR'])], axis=1); df
Out[77]:
JOINED_CO GENDER EXEC_FULLNAME GVKEY YEAR CONAME BECAMECEO \
5622 NaN MALE Ira A. Eichner 1004 1992 AAR CORP 19550101
5622 NaN MALE Ira A. Eichner 1004 1993 AAR CORP 19550101
5622 NaN MALE Ira A. Eichner 1004 1994 AAR CORP 19550101
5622 NaN MALE Ira A. Eichner 1004 1995 AAR CORP 19550101
5622 NaN MALE Ira A. Eichner 1004 1996 AAR CORP 19550101
5622 NaN MALE Ira A. Eichner 1004 1997 AAR CORP 19550101
5622 NaN MALE Ira A. Eichner 1004 1998 AAR CORP 19550101
5623 NaN MALE David P. Storch 1004 1992 AAR CORP 19961009
5623 NaN MALE David P. Storch 1004 1993 AAR CORP 19961009
5623 NaN MALE David P. Storch 1004 1994 AAR CORP 19961009
5623 NaN MALE David P. Storch 1004 1995 AAR CORP 19961009
5623 NaN MALE David P. Storch 1004 1996 AAR CORP 19961009
REJOIN LEFTOFC LEFTCO RELEFT REASON PAGE 1992 1993 1994 \
5622 NaN 19961001 19990531 NaN RESIGNED 79 1 0 0
5622 NaN 19961001 19990531 NaN RESIGNED 79 0 1 0
5622 NaN 19961001 19990531 NaN RESIGNED 79 0 0 1
5622 NaN 19961001 19990531 NaN RESIGNED 79 0 0 0
5622 NaN 19961001 19990531 NaN RESIGNED 79 0 0 0
5622 NaN 19961001 19990531 NaN RESIGNED 79 0 0 0
5622 NaN 19961001 19990531 NaN RESIGNED 79 0 0 0
5623 NaN NaN NaN NaN NaN 57 1 0 0
5623 NaN NaN NaN NaN NaN 57 0 1 0
5623 NaN NaN NaN NaN NaN 57 0 0 1
5623 NaN NaN NaN NaN NaN 57 0 0 0
5623 NaN NaN NaN NaN NaN 57 0 0 0
1995 1996 1997 1998
5622 0 0 0 0
5622 0 0 0 0
5622 0 0 0 0
5622 1 0 0 0
5622 0 1 0 0
5622 0 0 1 0
5622 0 0 0 1
5623 0 0 0 0
5623 0 0 0 0
5623 0 0 0 0
5623 1 0 0 0
5623 0 1 0 0
If you'd like to delete the YEARcolumn, then you could follow this up with del df['YEAR']. Or, drop the YEARcolumn from dfbefore calling concat:
如果您想删除该YEAR列，那么您可以使用del df['YEAR']. 或者，在调用之前删除YEAR列：dfconcat
df = pd.concat([df.drop('YEAR', axis=1), pd.get_dummies(df['YEAR'])], axis=1)
