Data Wrangling With Python - AI-Powered Learning for Developers

Gain insights into data wrangling using Python. Learn about cleaning, transforming, and organizing data with libraries like NumPy, pandas, and scikit-learn for data science and machine learning projects.

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

Get familiar with data wrangling, essential techniques, and Python libraries NumPy and pandas.

Course Introduction

Introduction to Data Wrangling

Look at transforming raw data into usable formats, improving quality, and applying core techniques.

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

Reading Data

Delve into reading and manipulating CSV, Excel, and local datasets using pandas.

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

Grasp the fundamentals of column fixing, data type conversion, string conversion, and coding challenges in standardization.

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

Syntax Errors and Irrelevant Data

Take a closer look at cleaning data by correcting typos, removing spaces, handling irrelevant data, and coding challenges.

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

See how it works to manage and resolve duplicate and missing data issues with Python.

Filtering and Sorting

6 Lessons

Master data filtering and sorting techniques in Python using pandas through practical examples.

Splitting, Combining, and Merging

5 Lessons

Step through splitting, joining, and merging DataFrames with hands-on coding challenges.

Handling Outliers

5 Lessons

Walk through outlier identification, advanced detection methods, and practical handling strategies in Python.

10.

Exporting Data

4 Lessons

Go hands-on with exporting DataFrames to CSV and Excel, and tackle coding challenges.

Humanitarian Aid Project

Project

11.

Conclusion

1 Lesson

Grasp the fundamentals of data wrangling using pandas and NumPy for effective data manipulation.

Course Author

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