Udemy – Mastering Data Analysis with Polars in Python: Crash Course 2024-3
Udemy – Mastering Data Analysis with Polars in Python: Crash Course 2024-3 Downloadly IRSpace
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Mastering Data Analysis with Polars in Python: Crash Course is a training course on data analysis with Polars in Python, published by Udemy Online Academy. Mastering Data Analysis with Polars in Python: Crash Course is an intensive program designed to introduce students to Polars, a powerful and fast DataFrame library for Python. This course focuses on teaching people how to efficiently manipulate and analyze large data sets using Polars, providing a performance-oriented alternative to Pandas. Key topics include data loading, filtering, aggregation, and transformation, along with advanced techniques for handling complex queries and optimizing data processing tasks. Learners will explore the benefits of Polars lazy execution model and how to apply it to efficient data pipelines.
This course covers data manipulation techniques such as filtering, aggregation, and transformation, with a focus on the performance benefits of Polar over Pandas. Learners will explore Polars’ lazy execution model for optimized data pipelines, gaining hands-on experience for efficiently managing large datasets and complex queries. Through hands-on exercises and hands-on examples, participants will develop the skills to perform high-performance data analysis, making Polars an invaluable tool in their data science toolbox. At the end of the course, learners will be equipped to perform large-scale data processing tasks with speed and efficiency using Polars.
What you will learn in Mastering Data Analysis with Polars in Python: Crash Course:
- Essential data processing techniques including filtering, aggregation and data transformation
- Mastery of advanced data manipulation tasks such as joining, grouping and windowing functions
- Skills to tackle complex data analysis challenges
- Using Polars for fast and efficient data analysis in Python
- Techniques for working with large CSV files using Polars
- Strategies to optimize memory usage and processing speed when dealing with large data sets
- and…
Course specifications
Publisher: Udemy
Instructors: Idan Chen
Language: English
Level: Introductory to Advanced
Number of Lessons: 32
Duration: 2 hours and 48 minutes
Course topics on 2024/4
Mastering Data Analysis with Polars in Python: Crash Course Prerequisites
Basic understanding of Python programming.
Familiarity with data structures like lists, dictionaries, and tuples.
Prior knowledge of data analysis concepts is beneficial but not required.
Access to a computer with Python and Polars library installed (installation instructions will be provided).
Pictures
Mastering Data Analysis with Polars in Python: Crash Course introduction video
Installation guide
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Subtitle: None
Quality: 720p
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896 MB
