Pandas Cookbook
Practical recipes for scientific computing, time series, and exploratory data analysis using Python
Created by William Ayd, Matthew Harrison
Explore practical techniques for working with pandas 2.x and learn how to tackle real-world data analysis tasks in Python. Get hands-on experience with data wrangling, visualization, and performance optimization to help you analyze and manipulate data efficiently. Discover how to turn raw data into meaningful insights using pandas' most powerful features.
Packt | Oct 2024 | 404 min
What You Will Learn
You will follow step-by-step instructions and detailed code explanations using Jupyter Notebooks. Each topic is broken down into practical recipes, allowing you to practice and apply new skills as you go. By working through real examples, you'll build confidence in handling a wide range of data analysis challenges.
Key Features
- Import, merge, and reshape large datasets for efficient analysis
- Apply advanced time series and SQL-like operations to real data problems
- Optimize memory usage and integrate pandas with tools like NumPy and databases
Target Audience
Designed for Python developers, data analysts, and data scientists who already understand the basics of Python and want to deepen their data manipulation skills. If you're looking to work more efficiently with structured data and master pandas' advanced capabilities, you'll find this course especially valuable.
