In this course, you’ll learn how to use Pandas index objects for advanced data analysis. You'll learn how to create and use numerical, interval, period, categorical, date-time, time-delta, and multi-indexing in Pandas to retrieve and manipulate data.
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.
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.
