Python for Data Tasks: Basic & Intermediate with Pandas and Polars Training Course

Python Fundamentals for Data Tasks for Government

• Installing Python and configuring the development environment for government use
• Language fundamentals: variables, data types, and control structures for efficient coding in a governmental context
• Writing and executing simple Python scripts to support public sector operations

File Handling: CSV and Excel for Government

• Reading and writing CSV files using the csv module and Pandas, tailored for government data sets
• Working with Excel files using openpyxl/xlrd and Pandas to manage governmental records
• Practical exercises: automating file conversions for improved data management in public sector applications

Introduction to Pandas for Government Data Analysis

• DataFrame basics: creation, indexing, selection, and filtering for government datasets
• Aggregation and grouping operations to derive insights from public sector data
• Common cleaning operations: handling missing values, duplicates, and type conversions in governmental databases

Introduction to Polars for Enhanced Performance in Government Data Processing

• Polars concepts and performance characteristics compared to Pandas, specifically for government data tasks
• Basic DataFrame operations in Polars to optimize governmental data workflows
• Use-case example: scenarios where Polars is preferred over Pandas for government applications

Advanced Data Transformation (Intermediate) for Government

• Complex joins, window functions, and pivot operations in Pandas to enhance governmental data analysis
• Efficient data processing patterns with Polars for optimizing public sector data workflows
• Chaining operations and optimizing memory usage for large-scale government datasets

Process Automation with Python for Government Operations

• Writing scripts to automate repetitive data tasks and ETL steps in governmental processes
• Scheduling scripts using OS schedulers or task schedulers for consistent public sector data management
• Implementing logging, error handling, and notifications for robust government data automation

Packaging Scripts and Best Practices for Government Use

• Creating executables with PyInstaller or similar tools to deploy scripts in a governmental setting
• Project structuring, virtual environments, and dependency management for secure and maintainable government applications
• Version control basics and documenting workflows to ensure transparency and accountability in public sector projects

Hands-on Mini-Project for Government Data Tasks

• End-to-end task: read raw files, clean and transform data, and produce outputs for government reporting
• Automate the workflow and package as a runnable script or executable for efficient public sector operations
• Review and improvements based on peer feedback to enhance governmental data practices

Summary and Next Steps for Government Data Professionals