Python Pandas Profiling - Why Data Profiling Is Important for You

Discover the power of pandas-profiling in this comprehensive 33-minute video tutorial. Learn how to generate detailed, interactive reports for your datasets with just a few lines of code. Explore the library's capabilities through hands-on demonstrations using the Titanic dataset, covering interactions, correlations, missing values, and more. Master advanced features like configuring metadata, customizing report details, and integrating profiling reports into Streamlit applications. Gain valuable insights into handling large datasets and optimizing profiling settings for efficiency. By the end of this tutorial, you'll be equipped to streamline your data analysis workflow and extract meaningful insights from your pandas datasets with ease.

- Video Start
- Video Content Intro
- Code & Jupyter Notebook Introduction
- Library Installation
- Pandas-profiling Library Introduction
- Demo with Titanic Dataset
- Demo with Titanic Dataset - Interactions
- Demo with Titanic Dataset - Correlations
- Demo with Titanic Dataset - Missing Values
- Saving HTML Report
- Profiling large dataset
- Minimal Profiling Reporting Setting
- Demo with Titanic Dataset - Config Metadata
- Demo with Titanic Dataset - Config Details
- Demo with Titanic Dataset - Config Param
- Demo with Titanic Dataset - View Widgets
- Demo with Titanic Dataset - Histogram Config
- Streamlit Application with Profiling Report
- Recap
- Credits