Passing Arguments to Series Apply Functions in Python Pandas

The pandas library provides the 'apply()' method to apply a function to each element of a Series. However, older versions of pandas do not allow additional arguments to be passed to the function.

Solution for Older Versions of Pandas:

To handle this limitation in older versions of pandas, you can use 'functools.partial()' or 'lambda' functions:

Using 'functools.partial()':

import functools
import operator

# Define a function with multiple arguments
def add_3(a, b, c):
    return a   b   c

# Create a partial function by binding extra arguments
add_3_partial = functools.partial(add_3, 2, 3)

# Apply the partial function to a series
series.apply(add_3_partial)

Using 'lambda':

# Create a lambda function to pass extra arguments to the apply method
lambda_func = lambda x: my_function(a, b, c, d, ..., x)

# Apply the lambda function to the series
series.apply(lambda_func)

Solution for Newer Versions of Pandas:

Since October 2017, pandas supports passing both positional and keyword arguments directly to the 'apply()' method:

series.apply(my_function, args=(2, 3, 4), extra_kw={"example": 5})

In this syntax, positional arguments are added after the element of the Series, while keyword arguments are passed as a dictionary.