- Python Pandas - Home
 - Python Pandas - Introduction
 - Python Pandas - Environment Setup
 - Python Pandas - Basics
 - Python Pandas - Introduction to Data Structures
 - Python Pandas - Index Objects
 - Python Pandas - Panel
 - Python Pandas - Basic Functionality
 - Python Pandas - Indexing & Selecting Data
 - Python Pandas - Series
 - Python Pandas - Series
 - Python Pandas - Slicing a Series Object
 - Python Pandas - Attributes of a Series Object
 - Python Pandas - Arithmetic Operations on Series Object
 - Python Pandas - Converting Series to Other Objects
 - Python Pandas - DataFrame
 - Python Pandas - DataFrame
 - Python Pandas - Accessing DataFrame
 - Python Pandas - Slicing a DataFrame Object
 - Python Pandas - Modifying DataFrame
 - Python Pandas - Removing Rows from a DataFrame
 - Python Pandas - Arithmetic Operations on DataFrame
 - Python Pandas - IO Tools
 - Python Pandas - IO Tools
 - Python Pandas - Working with CSV Format
 - Python Pandas - Reading & Writing JSON Files
 - Python Pandas - Reading Data from an Excel File
 - Python Pandas - Writing Data to Excel Files
 - Python Pandas - Working with HTML Data
 - Python Pandas - Clipboard
 - Python Pandas - Working with HDF5 Format
 - Python Pandas - Comparison with SQL
 - Python Pandas - Data Handling
 - Python Pandas - Sorting
 - Python Pandas - Reindexing
 - Python Pandas - Iteration
 - Python Pandas - Concatenation
 - Python Pandas - Statistical Functions
 - Python Pandas - Descriptive Statistics
 - Python Pandas - Working with Text Data
 - Python Pandas - Function Application
 - Python Pandas - Options & Customization
 - Python Pandas - Window Functions
 - Python Pandas - Aggregations
 - Python Pandas - Merging/Joining
 - Python Pandas - MultiIndex
 - Python Pandas - Basics of MultiIndex
 - Python Pandas - Indexing with MultiIndex
 - Python Pandas - Advanced Reindexing with MultiIndex
 - Python Pandas - Renaming MultiIndex Labels
 - Python Pandas - Sorting a MultiIndex
 - Python Pandas - Binary Operations
 - Python Pandas - Binary Comparison Operations
 - Python Pandas - Boolean Indexing
 - Python Pandas - Boolean Masking
 - Python Pandas - Data Reshaping & Pivoting
 - Python Pandas - Pivoting
 - Python Pandas - Stacking & Unstacking
 - Python Pandas - Melting
 - Python Pandas - Computing Dummy Variables
 - Python Pandas - Categorical Data
 - Python Pandas - Categorical Data
 - Python Pandas - Ordering & Sorting Categorical Data
 - Python Pandas - Comparing Categorical Data
 - Python Pandas - Handling Missing Data
 - Python Pandas - Missing Data
 - Python Pandas - Filling Missing Data
 - Python Pandas - Interpolation of Missing Values
 - Python Pandas - Dropping Missing Data
 - Python Pandas - Calculations with Missing Data
 - Python Pandas - Handling Duplicates
 - Python Pandas - Duplicated Data
 - Python Pandas - Counting & Retrieving Unique Elements
 - Python Pandas - Duplicated Labels
 - Python Pandas - Grouping & Aggregation
 - Python Pandas - GroupBy
 - Python Pandas - Time-series Data
 - Python Pandas - Date Functionality
 - Python Pandas - Timedelta
 - Python Pandas - Sparse Data Structures
 - Python Pandas - Sparse Data
 - Python Pandas - Visualization
 - Python Pandas - Visualization
 - Python Pandas - Additional Concepts
 - Python Pandas - Caveats & Gotchas
 
Pandas Series.str.center() Method
The Series.str.center() method in Pandas is used to pad both the left and right sides of strings in a Series or Index to a specified width.
This method ensures that the string is centered within the new width, with additional characters filled by a specified fill character. This operation is similar to the string method str.center() in Python.
Syntax
Following is the syntax of the Pandas Series.str.center() method −
Series.str.center(width, fillchar=' ')
Parameters
The Series.str.center() method accepts the following parameters −
- width: An integer specifying the minimum width of the resulting string. Additional characters will be filled with fillchar.
 - fillchar: A string specifying the character for filling, default is whitespace.
 
Return Value
The Series.str.center() method returns a new Series with the strings centered and padded to the specified width using the specified fill character.
Example 1
In this example, we demonstrate the basic usage of the Series.str.center() method by applying it to a Series of strings.
import pandas as pd
# Create a Series of strings
s = pd.Series(['dog', 'lion', 'panda'])
# Display the input Series
print("Input Series")
print(s)
# Center the strings with a width of 8 and fill character '.'
print("Series after calling center with width=8 and fillchar='.':")
print(s.str.center(8, fillchar='.'))
When we run the above code, it produces the following output −
Input Series 0 dog 1 lion 2 panda dtype: object Series after calling center with width=8 and fillchar='.': 0 ..dog... 1 ..lion.. 2 .panda.. dtype: object
Example 2
This example demonstrates how to use the Series.str.center() method to format the 'Animal' column in a DataFrame, by centering each animal name to a specified width with a custom fill character.
import pandas as pd
# Create a DataFrame
df = pd.DataFrame({'Animal': ['dog', 'lion', 'panda'], 'Legs': [4, 4, 2]})
print("Input DataFrame:")
print(df)
# Center the strings in the 'Animal' column with a width of 8 and fill character '-'
df['Animal'] = df['Animal'].str.center(8, fillchar='-')
print("DataFrame after applying center with width=8 and fillchar='-':")
print(df)
Following is the output of the above code −
Input DataFrame:
  Animal  Legs
0    dog     4
1   lion     4
2  panda     2
DataFrame after applying center with width=8 and fillchar='-':
    Animal  Legs
0  --dog---     4
1  --lion--     4
2  -panda--     2
Example 3
In this example, we apply the Series.str.center() method to an Index object. This showcases how you can use it to format the index labels in a DataFrame by centering them with a specified width and fill character.
import pandas as pd
# Create a DataFrame with an Index
df = pd.DataFrame({'Value': [1, 2, 3]}, index=['first', 'second', 'third'])
# Display the Input DataFrame
print("Input DataFrame:")
print(df)
# Center the index labels with a width of 10 and fill character '*'
df.index = df.index.str.center(10, fillchar='*')
# Display the Modified DataFrame
print("Modified DataFrame:")
print(df)
Output of the above code is as follows −
Input DataFrame:
        Value
first       1
second      2
third       3
Modified DataFrame:
            Value
**first***      1
**second**      2
**third***      3