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Duration 14 hours
Course Outline
Python Fundamentals for Data Workflows
- Setting up the development environment and installing Python.
- Core language concepts: variables, data types, and control structures.
- Developing and executing basic Python scripts.
File Management: CSV and Excel
- Processing CSV files using the csv module and Pandas.
- Handling Excel files via openpyxl/xlrd and Pandas.
- Practical drills: Automating file format conversions.
Getting Started with Pandas
- Foundations of DataFrames: creation, indexing, selection, and filtering.
- Executing aggregation and grouping operations.
- Standard cleaning tasks: handling missing values, duplicates, and type casting.
Introduction to Polars
- Core concepts of Polars and its performance advantages over Pandas.
- Executing basic DataFrame operations in Polars.
- Scenario analysis: Determining when to prefer Polars over Pandas.
Advanced Data Transformation (Intermediate Level)
- Performing complex joins, window functions, and pivot operations in Pandas.
- Implementing efficient data processing patterns with Polars.
- Optimizing memory usage through operation chaining.
Automating Processes with Python
- Developing scripts to automate repetitive data tasks and ETL steps.
- Scheduling scripts using OS or task schedulers.
- Implementing logging, error handling, and notification systems.
Script Packaging and Best Practices
- Building executables using PyInstaller or comparable tools.
- Structuring projects, managing virtual environments, and handling dependencies.
- Essentials of version control and documenting workflows.
Practical Mini-Project
- End-to-end workflow: Ingesting raw files, cleaning and transforming data, and generating outputs.
- Automating the entire workflow and packaging it as a runnable script or executable.
- Peer review and iterative improvements.
Conclusion and Future Directions
Requirements
- A foundational understanding of programming concepts or a strong motivation to learn them.
- Proficiency in using command-line interfaces or terminals for installing packages.
- Prior experience handling spreadsheet formats such as CSV and Excel.
Target Audience
- Data analysts and operations personnel looking to automate routine data tasks.
- Analytical engineers seeking lightweight solutions for ETL scripting.
- Professionals aiming to implement practical, Python-driven data workflows.
Testimonials (2)
everything was perfect
Florin Vrincianu
Course - Python Programming Fundamentals
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
