- Pandas - Install Python and Pandas
- Basic Data Structures in Pandas
- Loading and Saving Data using Pandas
- Exploring Data using pandas
- Correlation Analysis using pandas
- Handling Categorical Data and Unique Values using pandas
- Data Visualization using pandas
- Handling Missing Data in Python
- Strategies for Handling Missing Data
- Handling Missing Data - Example - Part 1
- Handling Missing Data - Example - Part 2
- Handling Missing Data - Example - Part 3 (Non-numeric Values)
- Handling Missing Data - Example - Part 4
- Data Transformation and Feature Engineering
- Converting Data Types in Python pandas
- Encoding Categorical Data in Python pandas
- Handling Date and Time Data in Python pandas
- Renaming Columns in Python pandas
- Filtering Rows in a DataFrame in Python
- Merging and Joining Datasets in Python pandas
- Sorting and Indexing Data for Efficient Analysis in Python
Renaming Columns in Python pandas
Changing column names in a pandas DataFrame is a common task, often done to make data more readable, comply with naming conventions, or prepare for data processing steps. Column names can be changed using the rename method or by directly assigning a new list of column names to the columns attribute of the DataFrame. The rename method is more flexible as it allows you to rename only specific columns without needing to specify all column names.
Here's an example showing how to rename columns in a DataFrame:
# Rename columns using the 'rename' method
loan_data_cleaned = loan_data_cleaned.rename(columns={
'CustomerName': 'ClientName',
'LoanAmount': 'Amount',
'LoanStartDate': 'StartDate',
'LoanEndDate': 'EndDate'
})
# Alternatively, to rename all columns directly:
# loan_data_cleaned.columns = ['NewCol1', 'NewCol2', 'NewCol3', ..., 'NewColN']
# Verify the changes
print(loan_data_cleaned.columns)
Related Downloads
Data Science in Finance: 9-Book Bundle
Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.
What's Included:
- Getting Started with R
- R Programming for Data Science
- Data Visualization with R
- Financial Time Series Analysis with R
- Quantitative Trading Strategies with R
- Derivatives with R
- Credit Risk Modelling With R
- Python for Data Science
- Machine Learning in Finance using Python
Each book includes PDFs, explanations, instructions, data files, and R code for all examples.
Get the Bundle for $39 (Regular $57)Free Guides - Getting Started with R and Python
Enter your name and email address below and we will email you the guides for R programming and Python.