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Learning the Polars DataFrame Library - Introduction and Hands-on Exploration

Offered By: Keith Galli via YouTube

Tags

Data Science Courses Data Analysis Courses Python Courses pandas Courses Data Manipulation Courses DataFrames Courses Kaggle Courses

Course Description

Overview

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Dive into a comprehensive tutorial on learning the Polars DataFrame library, a powerful alternative to Pandas. Explore hands-on exercises and practical examples as you discover efficient strategies for mastering new programming skills. Begin with an introduction to Polars, covering basic concepts and syntax. Progress through more advanced topics, including expressions, filters, and group-by operations. Compare Polars' performance benefits to Pandas, including handling large datasets. Gain insights into real-world applications and problem-solving techniques in data science. Benefit from a Q&A session addressing common concerns in Python data science, freelancing, and career development. Perfect for those looking to expand their data manipulation toolkit and improve their learning approach for new technologies.

Syllabus

- Random Banter
- Livestream Overview & General Learning Strategy
- Getting started with Polars
- I temporarily don't know how to share my screen
- Getting started with Polars in code
- Expressions in Polars Select, Filter
- Learning Polars vs Pandas Strategy
- Main Polars Concepts Exploring the Documentation
- Performance Benefits of Polars vs Pandas
- More complex Polars select context
- Exploring Polars Documentation with_columns, filters, group_by
- Groupby Example see comments for small correction
- Q&A: How long did it take you to learn Python for Data Science?
- Q&A: What laptop are you using?
- Q&A: Have you ever gotten stuck at work? What did you do?
- Q&A: Any advice on leetcoding?
- Performance Benefits of Polars Loading in 2gb file
- Q&A: How to get started with freelance projects?? & Upwork Strategy
- More Polars Exploration & Continued Learning Strategy
- Question & Answer Session


Taught by

Keith Galli

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