cartesian product in pandas

Question

I have two pandas dataframes:

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


        

Answer 1

As an alternative, one can rely on the cartesian product provided by itertools: itertools.product, which avoids creating a temporary key or modifying the index:

import numpy as np 
import pandas as pd 
import itertools

def cartesian(df1, df2):
    rows = itertools.product(df1.iterrows(), df2.iterrows())

    df = pd.DataFrame(left.append(right) for (_, left), (_, right) in rows)
    return df.reset_index(drop=True)

Quick test:

In [46]: a = pd.DataFrame(np.random.rand(5, 3), columns=["a", "b", "c"])

In [47]: b = pd.DataFrame(np.random.rand(5, 3), columns=["d", "e", "f"])    

In [48]: cartesian(a,b)
Out[48]:
           a         b         c         d         e         f
0   0.436480  0.068491  0.260292  0.991311  0.064167  0.715142
1   0.436480  0.068491  0.260292  0.101777  0.840464  0.760616
2   0.436480  0.068491  0.260292  0.655391  0.289537  0.391893
3   0.436480  0.068491  0.260292  0.383729  0.061811  0.773627
4   0.436480  0.068491  0.260292  0.575711  0.995151  0.804567
5   0.469578  0.052932  0.633394  0.991311  0.064167  0.715142
6   0.469578  0.052932  0.633394  0.101777  0.840464  0.760616
7   0.469578  0.052932  0.633394  0.655391  0.289537  0.391893
8   0.469578  0.052932  0.633394  0.383729  0.061811  0.773627
9   0.469578  0.052932  0.633394  0.575711  0.995151  0.804567
10  0.466813  0.224062  0.218994  0.991311  0.064167  0.715142
11  0.466813  0.224062  0.218994  0.101777  0.840464  0.760616
12  0.466813  0.224062  0.218994  0.655391  0.289537  0.391893
13  0.466813  0.224062  0.218994  0.383729  0.061811  0.773627
14  0.466813  0.224062  0.218994  0.575711  0.995151  0.804567
15  0.831365  0.273890  0.130410  0.991311  0.064167  0.715142
16  0.831365  0.273890  0.130410  0.101777  0.840464  0.760616
17  0.831365  0.273890  0.130410  0.655391  0.289537  0.391893
18  0.831365  0.273890  0.130410  0.383729  0.061811  0.773627
19  0.831365  0.273890  0.130410  0.575711  0.995151  0.804567
20  0.447640  0.848283  0.627224  0.991311  0.064167  0.715142
21  0.447640  0.848283  0.627224  0.101777  0.840464  0.760616
22  0.447640  0.848283  0.627224  0.655391  0.289537  0.391893
23  0.447640  0.848283  0.627224  0.383729  0.061811  0.773627
24  0.447640  0.848283  0.627224  0.575711  0.995151  0.804567