Enroll Course: https://www.udemy.com/course/analiza-danych-w-python-i-pandas/
Are you looking to dive into the world of Data Science? If you have a foundational understanding of Python and a general grasp of data analysis concepts (think Excel-level familiarity), then the Udemy course “Data Science: Analiza danych w Python i PANDAS” might be your perfect next step. This course, taught in Polish, is designed to equip you with the essential skills using the powerful Pandas library.
**Why Pandas?**
Pandas is the backbone of data manipulation in Python for data science. Whether you’re getting into machine learning or simply need to clean and process data, Pandas is indispensable. This course emphasizes practical application, with every lesson featuring quizzes and hands-on exercises, reinforcing the author’s belief that active learning is crucial.
**Course Structure and Content**
Clocking in at over 13 hours of video content, this course doesn’t shy away from detail, yet it focuses on the most critical aspects of data work. You’ll receive accompanying materials, including carefully selected datasets, to practice the commands you learn. The course begins with setting up your environment, primarily focusing on Windows but with notes for Linux and macOS users. It covers Jupyter Notebook setup, configuration, package management, and keyboard shortcuts, which, while potentially seeming like a detour when you’re eager to analyze data, are invaluable for independent problem-solving later on.
The core of the course delves into Pandas, starting with the fundamental `Data Series` object – understanding this is key to mastering other Pandas functionalities. You’ll then move on to `DataFrames`, which allow you to work with multiple columns and begin building your own analyses. The course covers data modification, including adding rows/columns and restructuring indices, essential for preparing data. Subsequent sections focus on advanced analysis techniques like multi-level indexing, pivot tables, data aggregation, and grouping. The importance of grouping and aggregation is highlighted for uncovering nuanced patterns within data, rather than just looking at overall averages.
Data often comes from multiple sources, so a dedicated section on merging data from different files is included, akin to joining tables in a database. While Pandas offers basic plotting capabilities, the course touches upon creating and customizing various charts, noting that the heavy lifting for visualizations is done by Matplotlib, a topic for another course. The course concludes with essential skills for exporting and importing data, including working with Excel files and data from the internet.
**Who is this course for?**
This is **not** a beginner’s course for absolute Python novices. A prerequisite is a basic understanding of Python programming. If you need to brush up on Python, the author recommends their “Python dla początkujących” course. Familiarity with Excel is also beneficial, as the course mirrors many Excel operations but with a Pythonic approach.
**Learning Experience**
The course is intensive and practical, with minimal theory. The video format allows you to easily rewind or adjust playback speed, enhancing your learning pace. The author emphasizes that practical application is the only way to truly learn, and this course is structured to facilitate exactly that.
**Recommendation**
If you’re ready to transition from basic Python to the practical world of data analysis and are comfortable with the prerequisites, “Data Science: Analiza danych w Python i PANDAS” is a highly recommended course. It provides a solid foundation in Pandas, preparing you for more advanced data science topics and subsequent courses in the author’s series, such as “Python dla średnio zaawansowanych.”
Enroll Course: https://www.udemy.com/course/analiza-danych-w-python-i-pandas/