“The beauty of Dataquest is that it starts at the most basic level, so a true beginner can understand the concepts”

Aaron Melton

Business Analyst @Aditi Consulting

Course overview

In this course, you’ll learn to use NumPy and pandas for data exploration, preparation, and analysis. You’ll start this course by learning how NumPy can streamline your data science workflow with vectorized operations, ndarrays, and Boolean indexing. You’ll then discover how pandas can super-charge your data exploration, preparation, and analysis. Finally, you’ll bring everything you’ve learned to a data analysis project to test your skills.

Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser. You’ll apply your skills to several guided projects involving realistic business scenarios to build your portfolio and prepare for your next interview.

Key skills

  • Analyzing data with NumPy and pandas
  • Implementing coding concepts such as vectorized operations and Boolean indexing
  • Optimizing your data science workflow and building proficiency in data analysis

Course outline

Introduction to Pandas and NumPy for Data Analysis [7 lessons]

Introduction to NumPy 2h

Lesson Objectives
  • Improve your workflow using vectorized operations
  • Select data from NumPy ndarrays
  • Analyze data using NumPy methods

Boolean Indexing with NumPy 2h

Lesson Objectives
  • Create Boolean arrays based on data values
  • Select specific rows and columns using Boolean arrays
  • Analyze data using Boolean indexing

Introduction to Pandas 2h

Lesson Objectives
  • Differentiate between pandas DataFrame and Series objects
  • Select data in pandas using axis labels
  • Generate a count of unique non-null values in a DataFrame column

Exploring Data with Pandas: Fundamentals 2h

Lesson Objectives
  • Explore data using common methods
  • Assign data in pandas using index labels
  • Analyze data using pandas

Exploring Data with Pandas: Intermediate 3h

Lesson Objectives
  • Select data in pandas by location
  • Create complex filters using Boolean masks in pandas
  • Analyze data using pandas

Data Cleaning Basics 2h

Lesson Objectives
  • Read files using different encodings
  • Extract and convert numeric values from string values
  • Resolve missing values

Guided Project: Exploring eBay Car Sales Data 3h

Lesson Objectives
  • Clean a dataset on your own
  • Employ new pandas methods
  • Present your analysis to support your code

Projects in this course

Guided Project: Exploring eBay Car Sales Data

For this project, we’ll assume the role of data analysts for a used car classifieds service to explore and clean a dataset of car listings from eBay Kleinanzeigen, a section of the German eBay website.

The Dataquest guarantee


Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.


We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.

Master skills faster with Dataquest

Go from zero to job-ready

Go from zero to job-ready

Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.

Build your project portfolio

Build your project portfolio

Build confidence with our in-depth projects, and show off your data skills.

Challenge yourself with exercises

Challenge yourself with exercises

Work with real data from day one with interactive lessons and hands-on exercises.

Showcase your path certification

Showcase your path certification

Impress employers by completing a capstone project and certifying it with an expert review.

Grow your career with

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Aaron Melton

Business Analyst at Aditi Consulting

“Dataquest starts at the most basic level, so a beginner can understand the concepts. I tried learning to code before, using Codecademy and Coursera. I struggled because I had no background in coding, and I was spending a lot of time Googling. Dataquest helped me actually learn.”


Jessica Ko

Machine Learning Engineer at Twitter

“I liked the interactive environment on Dataquest. The material was clear and well organized. I spent more time practicing then watching videos and it made me want to keep learning.”


Victoria E. Guzik

Associate Data Scientist at Callisto Media

“I really love learning on Dataquest. I looked into a couple of other options and I found that they were much too handhold-y and fill in the blank relative to Dataquest’s method. The projects on Dataquest were key to getting my job. I doubled my income!”

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