Course Outline

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

Requirements

  • Basic understanding of programming concepts or a willingness to learn
  • Comfort with using command-line or terminal interfaces for package installation
  • Experience working with spreadsheet formats (CSV/Excel)

Audience

  • Data analysts and operations staff automating data tasks for government
  • Analytical engineers requiring lightweight ETL scripting solutions
  • Professionals interested in implementing practical Python-based data workflows
 14 Hours

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