Greg

“I love that Dataquest explains, here’s why we do this, and here’s how we take this next step. That helped a lot and not every platform does that. The guided paths ensured I never started something I wasn’t prepared for and I didn’t waste time trying to figure out what was next.”

Greg Iannarella

Coordinator of Business Writing @Seton Hall University

Course overview

This course is for intermediate Python users, and it builds upon the essentials covered in our previous Python lessons. You’ll learn how to leverage Python to supercharge your data analysis workflow. You’ll learn how to manipulate, combine, transform, and merge data; manipulate strings; and work with missing values in Python — as well as new concepts and techniques to improve the speed and efficiency of your Python code.

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

  • Aggregating, combining, transforming, and cleaning data
  • Manipulating strings and working with regular expressions in Python
  • Combining, transforming, and reshaping datasets
  • Resolving missing data and duplicate data

Course outline

Data Cleaning and Analysis in Python [6 lessons]

Data Aggregation 2h

Lesson Objectives
  • Employ different techniques for aggregating data
  • Generate intuition for the groupby operation

Combining Data Using Pandas 2h

Lesson Objectives
  • Employ different techniques for combining data
  • Employ database-style joins and keys

Transforming Data with Pandas 2h

Lesson Objectives
  • Transform columns in pandas using custom functions
  • Reshape data to prepare it for analysis

Working with Strings In Pandas 2h

Lesson Objectives
  • Manipulate strings with pandas
  • Employ regular expressions

Working With Missing And Duplicate Data 2h

Lesson Objectives
  • Drop rows and columns with missing data
  • Impute values to replace missing data
  • Identify and drop duplicate rows

Guided Project: Clean and Analyze Employee Exit Surveys 4h

Lesson Objectives
  • Clean and analyze datasets
  • Expand your portfolio with pandas

Projects in this course

Guided Project: Clean and Analyze Employee Exit Surveys

For this project, we’ll assume the role of data analysts for the Department of Education, Training and Employment and the Technical and Further Education institute in Queensland, Australia to analyze employee exit surveys and uncover insights about why employees resign.

The Dataquest guarantee

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.

Money

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
Dataquest.

98%
of learners recommend
Dataquest for career advancement
4.85
Dataquest rating
SwitchUp Best Bootcamps
$30k
Average salary boost
for learners who complete a path
Aaron

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.”

Jessi

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

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!”

Join 1M+ data learners on
Dataquest.

1

Create a free account

2

Choose a learning path

3

Complete exercises and projects

4

Advance your career

Start learning today