Главная
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1
Introduction
2
Matts Background
3
Loading Data
4
Exploring Data Frame
5
Exploring Data Types
6
Lowering Memory Requirements
7
Expressions
8
Columns
9
Vertical Stacking
10
Transposing
11
Integers
12
Polar Share
13
Polar Documentation
14
Avoid Drop
15
Renaming columns
16
PLAll
17
Task
18
Troubleshooting
Description:
Explore the powerful Polars data manipulation library in this comprehensive 2-hour and 14-minute tutorial from PyCon US. Dive into a real-world dataset to learn common operations, understand key differences from Pandas, and discover techniques to optimize your data pipeline. Gain hands-on experience through provided notebooks and labs, covering topics such as data loading, DataFrame exploration, memory optimization, expressions, column manipulation, and troubleshooting. Understand Polars' unique features, potential feature gaps compared to Pandas, and learn best practices for efficient data analysis. Perfect for data scientists and analysts looking to expand their toolkit and enhance their data processing capabilities.

Getting Started with Polars

PyCon US
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