Effective Data Manipulation with pandas

Delve into 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.

Beginner

89 Lessons

24h

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

564 Playgrounds

17 Quizzes

This course includes

564 Playgrounds

17 Quizzes

Course Overview

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 consid...Show More

What You'll Learn

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

What You'll Learn

An understanding of efficient data manipulation techniques for working with data in pandas

Course Content

Introduction

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

Before We Start

Data Structures

Series Introduction NaN Values in Series 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

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

Introduction to DataFrames Similarities between Series and DataFrame Math Methods on DataFrames Quiz: DataFrames and Math Methods on DataFrames Exercise: DataFrames in pandas Solution: DataFrames in pandas Looping and Aggregation The apply() Method Exercise: Looping, Aggregation and apply() Method Solution: Looping, Aggregation, and apply() Method Columns Types, .assign, and Memory Usage Creating and Updating Columns Dealing with Missing and Duplicated Data Quiz: Missing and Duplicated Data Sorting Columns and Indexes Filtering and Indexing Operations Indexing by Position Indexing by Name Filtering with Function and .loc Line and Bar Plots Scatter, Area, and Stacked Bar Plots Exercise: Sorting, Columns, Filtering, and Indexing Operations.Solution: Sorting, Columns, Filtering, and Indexing Operations Exercise: Plotting Solution: Plotting Quiz: Sorting Columns, Filtering, and Indexing Operations.Reshaping DataFrames with Dummies Reshaping by Pivoting and Grouping Aggregations

Manipulating Data

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

1 Lesson

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

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