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Home » Ebooks & Tutorials » Technical » Database & SQL » Packt Publishing – Data Analysis with Pandas and Python

Packt Publishing – Data Analysis with Pandas and Python

12/11/2017 Learning for Life Leave a Comment

Packt Publishing – Data Analysis with Pandas and Python
English | Size: 2.03 GB
Category: CBTs


Analyze data quickly and easily with Python’s powerful panda library! All datasets included — beginners welcome!

An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world!. Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today.

Welcome to the most comprehensive Pandas course available on Udemy! An excellent choice for both beginners and experts looking to expand their knowledge on one of the most popular Python libraries in the world! Data Analysis with Pandas and Python offers 19+ hours of in-depth video tutorials on the most powerful data analysis toolkit available today. Lessons include: installing, sorting, filtering, grouping, aggregating, de-duplicating, pivoting, munging, deleting, merging, visualizing, and more! Why learn pandas? If you’ve spent time in a spreadsheet software like Microsoft Excel, Apple Numbers, or Google Sheets and are eager to take your data analysis skills to the next level, this course is for you!

Data Analysis with Pandas and Python introduces you to the popular Pandas library built on top of the Python programming language. Pandas is a powerhouse tool that allows you to do anything and everything with colossal data sets — analyzing, organizing, sorting, filtering, pivoting, aggregating, munging, cleaning, calculating, and more! I call it “Excel on steroids”!

What You Will Learn
• Perform a multitude of data operations in Python’s popular “pandas” library including
grouping, pivoting, joining and more!
• Learn hundreds of methods and attributes across numerous pandas objects
• Possess a strong understanding of manipulating 1D, 2D, and 3D data sets
• Resolve common issues in broken or incomplete data sets

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Database & SQL Data Analysis, Packt Publishing, Pandas, Python

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