Learn the best practices and efficient techniques to manipulate and reshape data using pandas.

Machine Learning Essentials

This module is a comprehensive guide to using pandas for data analysis. It covers a wide range of topics related to data manipulation, including filtering, merging, grouping, pivoting, and reshaping data. In this module, we’ll learn about the best practices and efficient techniques for working with data. We’ll encounter numerous examples of real-world data analysis problems and will gain hands-on experience with the pandas library to solve them effectively. This module will also cover performance considerations and provide insights on common pitfalls to avoid when using pandas. The module is suitable for both beginners and experienced users of pandas. It includes detailed explanations of pandas concepts and functions, as well as tips and tricks for optimizing our code. At the end of this module, we’ll be able to effectively handle data using pandas.

Effective Data Manipulation with pandas

Solve some problems related to looping, aggregation, and the apply() method.

Introduction

Series Deep Dive

DataFrames

Manipulating Data

Conclusion

Exercise: Looping, Aggregation and apply() Method

Problem 1