
- 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.capitalize() Method
The Series.str.capitalize() method in Pandas is used to capitalize the first character of each string in a Series or Index. This method is a convenient way to standardize the case of text data, ensuring that each string starts with an uppercase letter and the rest are in lowercase. This operation is similar to the string method str.capitalize() in Python.
Syntax
Following is the syntax of the Pandas Series.str.capitalize() method −
Series.str.capitalize()
Parameters
The Series.str.capitalize() method does not accept any parameters.
Return Value
The Series.str.capitalize() method returns a new Series with the first letter of each string capitalized and all other letters in lowercase.
Example 1
In this example, we demonstrate the basic usage of the Series.str.capitalize() method by applying it to a Series of strings.
import pandas as pd # Create a Series of strings s = pd.Series(['hi,', 'welcome to', 'tutorialspoint']) # Display the input Series print("Input Series") print(s) # Capitalize the first letter of each string print("Series after calling the Capitalize:") print(s.str.capitalize())
When we run the above code, it produces the following output −
Input Series 0 hi, 1 welcome to 2 tutorialspoint dtype: object Series after calling the Capitalize: 0 Hi, 1 Welcome to 2 Tutorialspoint dtype: object
Example 2
This example demonstrates how to use the Series.str.capitalize() method to format the 'Day' column in a DataFrame, converting each day's name to proper capitalization.
import pandas as pd # Create a DataFrame df = pd.DataFrame({'Day': ['mon', 'tue', 'wed', 'thu', 'fri'], 'Subject': ['Math', 'english', 'science', 'music', 'games']}) print("Input DataFrame:") print(df) # Capitalize the first letter of each day df.Day = df.Day.str.capitalize() print("DataFrame after applying Capitalize:") print(df)
Following is the output of the above code −
Input DataFrame: Day Subject 0 mon Math 1 tue english 2 wed science 3 thu music 4 fri games DataFrame after applying Capitalize: Day Subject 0 Mon Math 1 Tue english 2 Wed science 3 Thu music 4 Fri games
Example 3
In this example, we apply the Series.str.capitalize() method to an Index object. This showcases how you can use it to format the index labels in a DataFrame.
import pandas as pd # Create a DataFrame with an Index df = pd.DataFrame({'Value': [1, 2, 3]}, index=['first', 'second', 'third']) # Capitalize the first letter of each index label df.index = df.index.str.capitalize() print(df)
Output of the above code is as follows −
Value First 1 Second 2 Third 3