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Course Outline
Python Essentials for Data Tasks
- Installing Python and configuring the development environment.
- Core language concepts: variables, data types, and control structures.
- Authoring and executing simple Python scripts.
File Management: CSV and Excel
- Reading and writing CSV files via the csv module and Pandas.
- Handling Excel files using openpyxl/xlrd and Pandas.
- Practical exercises focused on automating file conversions.
Pandas Fundamentals
- DataFrame basics: creation, indexing, selection, and filtering.
- Aggregation and grouping techniques.
- Common cleaning operations: addressing missing values, duplicates, and type conversions.
Polars Basics
- Polars concepts and performance metrics compared to Pandas.
- Executing basic DataFrame operations in Polars.
- Case studies: determining when to prefer Polars over Pandas.
Advanced Data Transformation (Intermediate Level)
- Complex joins, window functions, and pivot operations in Pandas.
- Efficient data processing patterns utilizing Polars.
- Chaining operations and optimizing memory usage.
Automation with Python
- Developing scripts to automate repetitive data tasks and ETL steps.
- Scheduling scripts using OS schedulers or task schedulers.
- Implementing logging, error handling, and notification systems.
Script Packaging and Best Practices
- Creating executables using PyInstaller or similar tools.
- Project structuring, virtual environments, and dependency management.
- Foundations of version control and workflow documentation.
Practical Mini-Project
- End-to-end challenge: read raw files, clean and transform data, and generate outputs.
- Automate the workflow and package it as a runnable script or executable.
- Review and refinement based on peer feedback.
Recap and Future Directions
Requirements
- Basic understanding of programming concepts or a strong desire to learn.
- Confidence in using command-line or terminal environments for package installation.
- Experience working with spreadsheets (CSV/Excel).
Target Audience
- Data analysts and operations personnel looking to automate data tasks.
- Analytical engineers seeking lightweight ETL scripting solutions.
- Professionals interested in practical, Python-based data workflows.
14 Hours
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.
