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Duration 14 hours
Course Outline
Python Fundamentals for Data Tasks
- Installing Python and configuring the development environment.
- Language basics: variables, data types, and control structures.
- Writing and executing simple Python scripts.
File Handling: CSV and Excel
- Reading and writing CSV files using the csv module and Pandas.
- Managing Excel files with openpyxl/xlrd and Pandas.
- Practical exercises: Automating file conversion processes.
Introduction to Pandas
- DataFrame essentials: creation, indexing, selection, and filtering.
- Aggregation and grouping operations.
- Standard cleaning tasks: Handling missing values, duplicates, and type conversions.
Introduction to Polars
- Core Polars concepts and performance comparisons with Pandas.
- Basic DataFrame operations within Polars.
- Case study: Determining when to prefer Polars over Pandas.
Advanced Data Transformation (Intermediate)
- Complex joins, window functions, and pivot operations in Pandas.
- Efficient data processing patterns utilizing Polars.
- Chaining operations and optimizing memory usage.
Process Automation with Python
- Developing scripts to automate repetitive data tasks and ETL steps.
- Scheduling scripts via OS schedulers or task schedulers.
- Implementing logging, error handling, and notification systems.
Packaging Scripts and Best Practices
- Creating executables using PyInstaller or similar tools.
- Project structuring, virtual environments, and dependency management.
- Version control fundamentals and workflow documentation.
Hands-on Mini-Project
- End-to-end scenario: Ingest raw files, clean and transform data, and generate outputs.
- Automate the workflow and package it as a runnable script or executable.
- Review and refine solutions based on peer feedback.
Summary and Next Steps
Requirements
- Basic understanding of programming concepts or a strong willingness to learn.
- Confidence in using the command line or terminal for package installation.
- Experience working with spreadsheets (CSV/Excel).
Target Audience
- Data analysts and operations staff seeking to automate data tasks.
- Analytical engineers looking for lightweight ETL scripting solutions.
- Professionals interested in practical Python-based 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.
