Python 熊猫两个数据框交叉连接
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pandas two dataframe cross join
提问by Vity Lin
I can't find anything about cross join include the merge/join or some other. I need deal with two dataframe using {my function} as myfunc . the equivalent of :
我找不到任何关于交叉连接的信息，包括合并/连接或其他一些。我需要使用 {my function} 作为 myfunc 处理两个数据帧。相当于：
{
for itemA in df1.iterrows():
for itemB in df2.iterrows():
t["A"] = myfunc(itemA[1]["A"],itemB[1]["A"])
}
the equivalent of :
相当于：
{
select myfunc(df1.A,df2.A),df1.A,df2.A from df1,df2;
}
but I need more efficient solution: if used apply i will be how to implement them thx;^^
但我需要更有效的解决方案：如果使用 apply 我将如何实现它们 thx;^^
采纳答案by leroyJr
For the cross product, see this question.
对于叉积，请参阅此问题。
Essentially, you have to do a normal merge but give every row the same key to join on, so that every row is joined to each other across the frames.
本质上，您必须进行正常的合并，但为每一行提供相同的键以进行连接，以便每一行在帧中相互连接。
You can then add a column to the new frame by applying your function:
然后，您可以通过应用您的函数向新框架添加一列：
new_df = pd.merge(df1, df2, on=key)
new_df.new_col = newdf.apply(lambda row: myfunc(row['A_x'], row['A_y']), axis=1)
axis=1forces .applyto work across the rows. 'A_x' and 'A_y' will be the default column names in the resulting frame if the merged frames share a column like in your example.
axis=1强制跨行.apply工作。如果合并的框架共享一个像您的示例中的列，则 'A_x' 和 'A_y' 将是结果框架中的默认列名称。
回答by A.Kot
Create a common 'key' to cross join the two:
创建一个通用的“密钥”来交叉连接两者：
df1['key'] = 0
df2['key'] = 0
df1.merge(df2, how='outer')
