zaheer80 / data-analysis-and-exploration-with-pandas

Data Analysis and Exploration with Pandas, published by Packt

Data Analysis and Exploration with Pandas [Video]

This is the code repository for Data Analysis and Exploration with Pandas [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

Are you looking for a gigantic boost in your productivity? Are you searching for some interesting and fun tricks to solve your data problems? If so, then this course is indeed a perfect choice for you. This course provides you with unique, idiomatic, and amazing solutions for both fundamental and advanced data manipulation tasks with pandas. Some solutions focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. A few others will delve into a particular dataset, and let you uncover new and unexpected insights along the way.

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This course guides you, as if you were looking over the shoulder of an expert, through practical situations that you are highly likely to encounter. Many advanced solutions combine several different features across the pandas library to generate results.

What You Will Learn

• Master the fundamentals of pandas to quickly begin exploring any dataset
• Explore the most crucial and common operations that you will perform during data analysis
• Build customized functions to apply to your groups.
• Restructure and tidy data to make data analysis and visualization easier
• Prepare real-world messy datasets for machine learning
• Combine and merge data from different sources through pandas SQL-like operations

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
Fundamental knowledge of Python.
It is assumed that the viewer is familiar with all the common built-in data containers in Python, such as lists, sets, dictionaries, and tuples.

Technical Requirements

This course has the following software requirements:
Anaconda 4.3
Jupyter Notebook
Python 3.x
Pandas 0.20.1

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