To build any business solution using data, the first step that you need to perform is data analysis. Pandas is a Python library that has numerous functionalities to simplify data analysis. Pandas Index objects offer some of these advanced functionalities to make data analysis easier. In this course, Index Objects with Pandas, you’ll learn how to use Pandas index objects for advanced data analysis. First, you’ll learn the basics of data-frames and various indexing strategies in Pandas. Next, you’ll discover how to create and use numerical, interval, period, and categorical indexing in Pandas to retrieve data from a data-frame. Then, you’ll see how to use date-time and time-delta indexing to extract and manipulate time-series data. Finally, you’ll dive into how to use multi-indexing in Pandas to organize data hierarchically.
Author Name: Biswanath Halder
Author Description:
Biswanath is a Data Scientist who has around nine years of working experience in companies like Oracle, Microsoft, and Adobe. He has extensive knowledge of Machine Learning, Deep Learning, and Reinforcement Learning. He specializes in applying Machine Learning and Deep Learning techniques in complex business applications related to computer vision and natural language processing. He is also a freelance educator and teaches Statistics, Mathematics, and Machine Learning. He holds a Master’s degre… more

Table of Contents

• Course Overview
  1min
• Introduction to Indexing Objects in Pandas
  11mins
• Pandas Index Objects for Time Series Data
  18mins
• Interval, Categorical, and Period Indexing in Pandas
  16mins
• Multi-indexing in Pandas
  9mins