Pandas Series.str.lower() Method

The Series.str.lower() method in in Python Pandas library is used to convert strings in a Series or Index to lowercase. This method is useful for text normalization and data preprocessing, as it ensures consistency in text data by converting all characters to lowercase.

Using this method can help in performing case-insensitive comparisons and analyses more effectively. And this is equivalent to Python's built-in str.lower() method and is commonly used in data cleaning and preprocessing tasks.

Syntax

Following is the syntax of the Pandas Series.str.lower() method −

Series.str.lower()

Parameters

The Pandas Series.str.lower() method does not accept any parameters.

Return Value

The Series.str.lower() method returns a Series or Index of the same shape, where each string has been converted to lowercase. This means that all characters in each string are converted to their lowercase form.

Example 1

Let's look at a basic example to understand how the Series.str.lower() method works −

import pandas as pd

# Create a Series
s = pd.Series(['Hello', 'WORLD', 'Pandas'])

# Display the input Series
print("Input Series")
print(s)

# Apply the lower method
print("Series after applying the lower:")
print(s.str.lower())

When we run the above program, it produces the following result −

Input Series
0    Hello
1    WORLD
2    Pandas
dtype: object

Series after applying the lower:
0    hello
1    world
2    pandas
dtype: object

Example 2

In this example, we'll demonstrate the use of the Series.str.lower() method in a DataFrame −

import pandas as pd

# Create a DataFrame
df = pd.DataFrame({'Name': ['Alice', 'Bob', 'CHARLIE'], 'Role': ['ADMIN', 'User', 'Manager']})

# Print the original DataFrame
print("Input DataFrame")
print(df)

# Apply the lower method to the 'Role' column
df['Role'] = df['Role'].str.lower()

# Print the modified DataFrame
print("Modified DataFrame:")
print(df)

Following is the output of the above code −

Input DataFrame
    Name     Role
0  Alice    ADMIN
1    Bob     User
2  CHARLIE  Manager

Modified DataFrame
    Name     Role
0  Alice    admin
1    Bob     user
2  CHARLIE  manager

Example 3

Let's see another example where we apply Series.str.lower() method to an Index object of the pandas DataFrame.

import pandas as pd

# Create a DataFrame with an Index
df = pd.DataFrame({'Value': [1, 2, 3]}, index=['First', 'SECOND', 'THIRD'])

# Print the original DataFrame
print("Original DataFrame:")
print(df)

# Apply lower to the DataFrame index labels
df.index = df.index.str.lower()

# Print the modified DataFrame
print("Modified DataFrame:")
print(df)

Output of the above code is as follows −

Original DataFrame:
        Value
First       1
SECOND      2
THIRD       3
Modified DataFrame:
        Value
first       1
second      2
third       3