Data Wrangling With Python - AI-Powered Learning for Developers

Beginner

47 Lessons

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Project

65 Playgrounds

29 Challenges

9 Quizzes

This course includes

1 Project

65 Playgrounds

29 Challenges

9 Quizzes

Course Overview

Data wrangling is cleaning, transforming, and organizing data for further analysis. In this course, you will learn how to use Python to effectively wrangle and prepare data for use in data science and machine learning projects. Throughout the course, you will learn about the common challenges that arise when working with data and how to overcome them. You will use Python and several libraries commonly used in data wrangling, including NumPy and pandas. Then, you will learn how to use pandas to clean, trans...Show More

What You'll Learn

Understanding of data wrangling and its application in developing data solutions

A working knowledge of common data wrangling challenges and their solutions

Hands-on experience applying data wrangling techniques using Python to prepare data for further analysis

Familiarity with the core components of data wrangling and the ability to differentiate between data wrangling techniques to understand their suitability

Hands-on experience with datasets to practice the data wrangling techniques in a mini project at the end of the course

What You'll Learn

Understanding of data wrangling and its application in developing data solutions

Course Content

About This Course

Course Introduction

Introduction to Data Wrangling

Data Wrangling Applications of Data Wrangling How to Apply Data Wrangling Quiz Yourself: Introduction to Data Wrangling

Reading Data

Loading a CSV Dataset From a URL Loading an Excel Dataset into a DataFrame Loading a Dataset Locally Coding Challenges on Reading Data Quiz Yourself: Reading Data

Standardization

Fixing the Columns Data Type Conversion String Conversion Coding Challenges on Standardization Quiz Yourself: Standardization

Syntax Errors and Irrelevant Data

Spelling Mistakes and Typos Leading and Trailing Spaces Handling Irrelevant Data Coding Challenges on Syntax Errors and Irrelevant Data Quiz Yourself: Syntax Errors and Irrelevant Data

Duplicate and Missing Data

6 Lessons

Filtering and Sorting

6 Lessons

Splitting, Combining, and Merging

5 Lessons

Handling Outliers

5 Lessons

Exporting Data

4 Lessons

Humanitarian Aid Project

Project

Conclusion

1 Lesson

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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