madel2040 / data-analysis-with-pandas-and-python

Code Repository for Data Analysis with Pandas and Python(v), Published by Packt

Data Analysis with Pandas and Python [Video]

This is the code repository for Data Analysis with Pandas and Python [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

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

• Understand the concept of Block algorithms and how Dask leverages it to load large data.
• Implement various example using Dask Arrays, Bags, and Dask Data frames for efficient parallel computing
• Combine Dask with existing Python packages such as NumPy and Pandas
• See how Dask works under the hood and the various in-built algorithms it has to offer
• Leverage the power of Dask in a distributed setting and explore its various schedulers
• Implement an end-to-end Machine Learning pipeline in a distributed setting using Dask and scikit-learn
• Use Dask Arrays, Bags, and Dask Data frames for parallel and out-of-memory computations

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
Data analysts and business analysts, Excel users looking to learn a more powerful software for data analysis

Technical Requirements

This course has the following software requirements:
NA

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