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Effective Data Manipulation with pandas

Learn effective data manipulation with pandas. Discover filtering, merging, grouping, and reshaping techniques through hands-on examples, best practices, and performance tips for real-world analysis.

4.8

89 Lessons

24h

Updated 4 months ago

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LEARNING OBJECTIVES

An understanding of efficient data manipulation techniques for working with data in pandas
Working knowledge of different techniques for handling missing data in pandas
The ability to reshape and pivot data
Hands-on experience of the best practices for working with pandas

Learning Roadmap

89 Lessons17 Quizzes4 Challenges

Introduction

Get familiar with pandas data structures for efficient data manipulation in Python.

Similarities in pandas and NumPy

Categorical Data in pandas

Exercise: Series in pandas

Solution: Series in pandas

Summary

Quiz: pandas Series

Series Deep Dive

Unpack the core of pandas Series manipulation, covering attributes, operations, and data cleaning.

DataFrames

29 Lessons

Examine building, manipulating, and visualizing DataFrames in pandas for effective data analysis.

Manipulating Data

21 Lessons

Grasp the fundamentals of manipulating and reshaping data, handling time series, joins, and exporting formats.

Wrapping Up

Explore continuous improvement in data analysis, from understanding data to engaging in real-world projects.

Conclusion

Appendix

Follow the process of installing and setting up pandas for Python projects.

Installation

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

ABOUT THIS COURSE

The course 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 course, you’ll learn about the best practices and efficient techniques for working with data. You’ll be provided with numerous examples of real-world data analysis problems and gain hands-on experience with the pandas library to solve them effectively. This course will also cover performance considerations and provide insights on common pitfalls to avoid when using pandas. The course 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 your code. By the time you’re done with this course, you’ll be able to effectively handle data using pandas.

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