Essential Guide to Python Pandas

A Python Pandas crash course to teach you all the essentials to get started with data analytics

Description

elcome to our Pandas crash course! This course is designed to provide you with a practical guide to using Pandas, the popular data manipulation library in Python. We’ve included real-life examples and reusable code snippets to help you quickly apply what you learn to your own data analysis projects.

Throughout this course, you will learn how to:

• Describe the Anatomy of Pandas Data Structures. This includes Pandas DataFrames, Series, and Indices.
• Implement several methods to get data into and from Pandas DataFrames. These methods include Python Native Data Structures, Tabular data files, API queries and JSON format, web scraping, and more.
• Describe any information within a Pandas DataFrame. This will help you to identify data problems such as having missing values or using incorrect data types.
• Understand Pandas Data Types and the correct use case for each type.
• Perform Data manipulation and cleaning. This part includes fixing data types, handling missing values, removing duplicate records, and many more.
• Merge & Join multiple datasets into Pandas DataFrames
• Perform Data Summarization & Aggregation within any DataFrame
• Create different types of Data Visualization
• Update Pandas Styling Settings
• Conduct a Data Analysis Project using Pandas library to collect and investigate COVID-19 infection, and the consequent lockdown in different countries.

In addition to the course materials, you’ll also have free access to a Jupyter Notebook with all of the code examples covered in this course, as well as a free e-book in PDF format. By the end of this course, you’ll have a solid understanding of how to use Pandas to perform data manipulation tasks and analyze data.

Who this course is for:

• This course is for aspiring data professionals and Python developers who want to learn how to process data in Pandas.