How to cross join (cartesian product) two Series?-CodePudding

Consider the following two series.

Let x be:

x
a   10
b   20
c   30
Name: x_value

And let y be:

y
d   100
e   200
Name: y_value

Ideally, the result would have a MultiIndex along with the cartesian product of the series' cross values:


      x_value y_value
x  y
a  d    10      100
   e    10      200
b  d    20      100
   e    20      200
c  d    30      100
   e    30      200

I have seen similar questions (e.g. cartesian product in pandas) about cross merge, but I haven't found anything about Series so far (let alone a MultiIndex of initial indices approach).

The part that seems troublesome to me is how I'd get to work with Series, instead of DataFrames.

CodePudding user response：

pd.merge() works on Series, but it doesn't keep the index.

df = pd.merge(x, y, how='cross')
df

   x_value  y_value
0       10      100
1       10      200
2       20      100
3       20      200
4       30      100
5       30      200

You can just make the MultiIndex yourself:

df.index = pd.MultiIndex.from_product([x.index, y.index], names=['x', 'y'])
df

     x_value  y_value
x y                  
a d       10      100
  e       10      200
b d       20      100
  e       20      200
c d       30      100
  e       30      200

Docs: pd.MultiIndex.from_product()

CodePudding user response：

Another solution is to use reset_index and merge, then set_index multiindex:

s1 = pd.Series([10,20,30], index=[*'abc'], name='x_values')
s2 = pd.Series([100, 200], index=[*'de'], name='y_values')

s1.reset_index().merge(s2.reset_index(), how='cross').set_index(['index_x', 'index_y'])

Output:

                 x_values  y_values
index_x index_y                    
a       d              10       100
        e              10       200
b       d              20       100
        e              20       200
c       d              30       100
        e              30       200