combine(self, other, func, fill_value=None) -> 'Series'

Combine the Series and other using func to perform elementwise selection for combined Series. :None:None:`fill_value` is assumed when value is missing at some index from one of the two objects being combined.

Parameters

other : Series or scalar

The value(s) to be combined with the Series .

func : function

Function that takes two scalars as inputs and returns an element.

fill_value : scalar, optional

The value to assume when an index is missing from one Series or the other. The default specifies to use the appropriate NaN value for the underlying dtype of the Series.

Returns

Series

The result of combining the Series with the other object.

Combine the Series with a Series or scalar according to func .

See Also

Series.combine_first

Combine Series values, choosing the calling Series' values first.

Examples

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

This example is valid syntax, but we were not able to check execution

>>> s1 = pd.Series({'falcon': 330.0, 'eagle': 160.0})
... s1
falcon    330.0
eagle     160.0
dtype: float64

This example is valid syntax, but we were not able to check execution

>>> s2 = pd.Series({'falcon': 345.0, 'eagle': 200.0, 'duck': 30.0})
... s2
falcon    345.0
eagle     200.0
duck       30.0
dtype: float64

Now, to combine the two datasets and view the highest speeds of the birds across the two datasets

This example is valid syntax, but we were not able to check execution

>>> s1.combine(s2, max)
duck        NaN
eagle     200.0
falcon    345.0
dtype: float64

In the previous example, the resulting value for duck 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.

This example is valid syntax, but we were not able to check execution

>>> s1.combine(s2, max, fill_value=0)
duck       30.0
eagle     200.0
falcon    345.0
dtype: float64

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

pandas.core.series.Series.combine_first

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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File: /pandas/core/series.py#3103
type: <class 'function'>
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