pandas 的笛卡尔积 [英] cartesian product in pandas

问题描述

我有两个熊猫数据框:

from pandas import DataFrame
df1 = DataFrame({'col1':[1,2],'col2':[3,4]})
df2 = DataFrame({'col3':[5,6]})     

获得笛卡尔积的最佳实践是什么(当然不用像我这样明确地写出来)?

What is the best practice to get their cartesian product (of course without writing it explicitly like me)?

#df1, df2 cartesian product
df_cartesian = DataFrame({'col1':[1,2,1,2],'col2':[3,4,3,4],'col3':[5,5,6,6]})

推荐答案

如果每行都有一个重复的键，则可以使用merge生成笛卡尔积(就像在SQL中一样).

If you have a key that is repeated for each row, then you can produce a cartesian product using merge (like you would in SQL).

from pandas import DataFrame, merge
df1 = DataFrame({'key':[1,1], 'col1':[1,2],'col2':[3,4]})
df2 = DataFrame({'key':[1,1], 'col3':[5,6]})

merge(df1, df2,on='key')[['col1', 'col2', 'col3']]

输出:

   col1  col2  col3
0     1     3     5
1     1     3     6
2     2     4     5
3     2     4     6

有关文档，请参见此处: http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra

See here for the documentation: http://pandas.pydata.org/pandas-docs/stable/merging.html#brief-primer-on-merge-methods-relational-algebra

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