Pandas Series.apply() Tutorial

In this tutorial, we'll explore the Series.apply() method in Pandas, which is used to apply a function along the axis of a Pandas Series, with well detailed example programs.

The syntax of Series.apply(func, convert_dtype=True, args=(), **kwds) is:

Series.apply(func, convert_dtype=True, args=(), **kwds)

where

Parameter	Description
func	The function to apply to each element in the Series.
convert_dtype	If True, infer the datatype of the result to be the same as the input Series. Default is True.
args	Additional arguments to pass to the function func.
**kwds	Additional keyword arguments to pass to the function func.

The Series.apply() method applies the function func to each element in the Series and returns a new Series with the results.

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Examples for Pandas Series.apply() function

1. Apply a custom function to double each element in the Series

In this example, we'll take a series of integer values in int_series variable, and use Series.apply() to apply a custom function that doubles each element in the int_series.

Python Program

import pandas as pd

# Create a series
series = pd.Series([10, 20, 30, 40, 50])

# Define a custom function to double each element
def double_element(x):
    return x * 2

# Apply the custom function using apply()
result = series.apply(double_element)

# Print original series and result
print("Original Series:")
print(series)
print("\nAfter applying the function:")
print(result)

Output

Original Series:
0    10
1    20
2    30
3    40
4    50
dtype: int64

After applying the function:
0     20
1     40
2     60
3     80
4    100
dtype: int64

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2. Apply a lambda function to square each element in the series

In this example, we'll use Series.apply() to apply a lambda function that squares each element in the given Series.

Python Program

import pandas as pd

# Create a series
series = pd.Series([10, 20, 30, 40, 50])

# Apply the custom function using apply()
result = series.apply(lambda x: x**2)

# Print original series and result
print("Original Series:")
print(series)
print("\nAfter applying the function:")
print(result)

Output

Original Series:
0    10
1    20
2    30
3    40
4    50
dtype: int64

After applying the function:
0     100
1     400
2     900
3    1600
4    2500
dtype: int64

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Summary

In this tutorial, we've covered the Series.apply() method in Pandas, which allows you to apply a function to each element in a Series.