Welcome to the Introduction to Pandas repository! This repository is designed to provide an accessible and hands-on guide for learning the basics of the Pandas library in Python. Whether you're a beginner or someone looking to refresh your knowledge, this repo will walk you through essential concepts, tools, and techniques to work with data efficiently using Pandas.
Key Topics Covered:
-DataFrames & Series: Learn how to create, manipulate, and access data using Pandas' core data structures. -Data Cleaning & Transformation: Master techniques to clean, filter, and transform datasets. -Handling Missing Data: Learn how to identify, fill, or drop missing values in your datasets. -GroupBy Operations: Understand how to group data and perform aggregate functions like mean, sum, etc. -Data Merging & Joining: Learn how to combine multiple datasets using various methods like merge(), concat(), and join(). -Time Series Data: Explore how to handle time-based data, including date parsing, resampling, and shifting. -Data Visualization: Introduction to basic plotting and visualizing data directly from Pandas with built-in support.
Features:
-Interactive Jupyter Notebooks: Contains practical examples and code snippets that you can run and experiment with. -Clear Explanations: Simple and easy-to-understand descriptions of each concept. -Beginner-Friendly: Perfect for those new to data analysis and those who want to learn Pandas in a step-by-step manner.