How to Apply a Function with Arguments to a Pandas Series?

Applying a Function with Arguments to a Pandas Series

Problem:

You need to apply a function to a pandas series with additional arguments. However, the pandas apply() method only accepts a function with a single argument.

Solution:

Newer Versions of Pandas (Post-October 2017):

pandas apply() has been updated to support positional and keyword arguments. To pass parameters, use the following syntax:

<code class="python">my_series.apply(your_function, args=(param1, param2, ...), extra_kw=arg1)</code>

Older Versions of Pandas:

1. Using functools.partial:

Create a partial function using functools.partial(func, *args, **kwargs) to bind additional arguments to your function:

<code class="python">add_3 = functools.partial(operator.add, 3)
my_series.apply(add_3)</code>

2. Using a lambda expression:

Pass a lambda function that incorporates the additional arguments:

<code class="python">my_series.apply(lambda x: your_func(x, arg1, arg2, ...))</code>

3. Creating a custom function:

Define a custom function that accepts all necessary arguments, including the elements of the series as the first parameter:

<code class="python">def my_custom_func(x, arg1, arg2, ...):
    return ...

my_series.apply(my_custom_func, args=(arg1, arg2, ...))</code>

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