How to Pass Additional Arguments to apply() in Python Pandas?

Passing Additional Arguments to apply() in Python Pandas

Applying user-defined functions to Pandas series often requires passing additional arguments. While early versions of Pandas did not allow this, newer versions provide support for argument passing.

Updated Approach (Pandas >= 1.0)

As of Pandas 1.0 and later, you can directly pass extra arguments using the apply() method.

<code class="python">my_series.apply(your_function, args=(2, 3, 4), extra_kw=1)</code>

Arguments passed using args are added after the series element, while keyword arguments can be passed using extra_kw.

Workaround for Older Versions

For versions prior to Pandas 1.0:

Method 1: Using functools.partial

This method allows you to create a partially applied function that binds any desired arguments.

<code class="python">import functools
import operator

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

Method 2: Using a Lambda Function

Lambda functions can also be used to pass arguments.

<code class="python">my_series.apply((lambda x: your_func(a, b, c, d, ..., x)))</code>

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