Examples
Consider 2 Datasets s1 and s2 containing highest clocked speeds of different birds.

In [1]:
import numpy as np
import pandas as pd
In [2]:
s1 = pd.Series({'eagle': 320.0, 'parrot': 120.0})
s1
Out[2]:
eagle     320.0
parrot    120.0
dtype: float64

In [3]:
s2 = pd.Series({'eagle': 335.0, 'parrot': 180.0, 'sparrow': 100.0})
s2
Out[3]:
eagle      335.0
parrot     180.0
sparrow    100.0
dtype: float64

In [4]:
Now, to combine the two datasets and view the highest speeds of the birds across the two datasets
  File "<ipython-input-4-a144bc87c1a0>", line 1
    Now, to combine the two datasets and view the highest speeds of the birds across the two datasets
                  ^
SyntaxError: invalid syntax
In [ ]:
s1.combine(s2, max)

In the previous example, the resulting value for sparrow is missing, because the maximum of a NaN and a float is a NaN.
So, in the example, we set fill_value=0, so the maximum value returned will be the value from some dataset.

In [ ]:
s1.combine(s2, max, fill_value=0)