Python | Pandas Series.replace()

Introduction

In data analysis and manipulation tasks, it is common to encounter a need to replace specific values in a column or series of data. The Series.replace() function in the Pandas library provides a convenient way to replace values in a Pandas Series object with other specified values.

Syntax

The syntax of the Series.replace() function is as follows:

Series.replace(to_replace=None, value=None, inplace=False, limit=None, regex=False, method='pad')

Parameters

The Series.replace() function accepts several parameters:

• to_replace: Specifies the value or list of values to be replaced.
• value: The value or list of values to replace the to_replace values with.
• inplace: If set to True, replaces the values in the original Series itself. Otherwise, returns a new replaced Series.
• limit: Specifies the maximum number of replacements to perform. A value of None represents no limit.
• regex: If set to True, treats the to_replace parameter as a regular expression pattern.
• method: Determines the method to use when replacing values. The default 'pad' method replaces values with the previous value.

Examples

Let's consider some examples to understand the usage of the Series.replace() function.

Example 1: Replace Single Value

import pandas as pd

data = pd.Series([10, 20, 30, 40, 50])
data.replace(30, 35)

Output:

0    10
1    20
2    35
3    40
4    50
dtype: int64

Example 2: Replace Multiple Values

import pandas as pd

data = pd.Series([10, 20, 30, 40, 50])
data.replace([30, 40], [35, 45])

Output:

0    10
1    20
2    35
3    45
4    50
dtype: int64

Example 3: Replace using Dictionary

import pandas as pd

data = pd.Series([10, 20, 30, 40, 50])
data.replace({30: 35, 40: 45})

Output:

0    10
1    20
2    35
3    45
4    50
dtype: int64

Conclusion

The Series.replace() function in Pandas is a powerful tool for replacing specific values in a Pandas Series object. With its flexible options and methods, it allows for easy replacement of single or multiple values based on user-defined criteria.