Polars Tutorial: Blazingly Fast Exploratory Data Analysis in Python скачать в хорошем качестве

Polars Tutorial: Blazingly Fast Exploratory Data Analysis in Python

Polars is a Python package (written in Rust) for working with DataFrames. Think Pandas, but faster. Much faster! In this tutorial, I'll explore basics of Polars and will compare it against Pandas - both in speed and syntax. This is a notebook walkthrough video, so you'll be able to follow along easily with the links below. Links: Notebook link - https://github.com/aruberts/tutorials... Dataset link - https://www.kaggle.com/datasets/datas... Medium blog -   / b2ec500a1008   Polars documentation - https://pola-rs.github.io/polars/py-p... 0:00 Intro 0:08 Pandas vs Polars 1:01 Goal of the video 1:27 Setup 2:43 Notebook structure 4:03 Installing Polars 4:46 Set Polars configs 5:43 Reading data with Polars 6:18 DataFrame basic exploration 7:34 Column selection 10:52 DataFrame filtering 12:42 DataFrame quality checks (checking for NAs and static) 15:55 Data cleaning and pre-processing 18:55 Univariate analysis (value counts, mean, median, etc.) 21:35 Multivariate analysis (groupby, aggregates) 27:14 Custom functions with Polars 32:00 Saving Polars DataFrame 32:20 Summary