- Free
pandas in 30 days
Why learn pandas?
pandas is a powerful, open source Python library for data analysis, manipulation, and visualization.
If you're working with data in Python and you're not using pandas, you're probably working too hard!
There are many things to like about pandas: It's well-documented, has a huge amount of community support, is under active development, and plays well with other Python libraries.
There are also things you might NOT like: pandas has an overwhelming amount of functionality (so it's hard to know where to start), and it provides too many ways to accomplish the same task (so it's hard to figure out the best practices).
That's why I created this course! I've been using and teaching pandas for 9+ years, and so I know how to explain pandas in a way that is understandable even to beginners.
Who should take this course?
This is the perfect course for you if:
You're new to the pandas library and you want to learn the fundamentals
You have some experience with pandas, but you want to fill in the gaps in your knowledge
You want to learn the best practices for data analysis with pandas in 2025
What topics are covered in the course?
Foundational topics:
What is pandas?
Reading data into pandas
Series and DataFrame objects
Selecting columns
Creating columns
Renaming columns
Removing columns
Filtering rows by one or more criteria
Sorting by index or values
Methods and attributes
Data exploration
Intermediate topics:
Plotting with pandas
Data analysis by category
Changing data types
String manipulation
Working with dates and times
Working with categorical data
Handling missing values
Handling duplicate data
Selecting multiple rows and columns
In-place operations
Using and setting the index
Understanding the axis
Applying functions
Customizing the display
Advanced topics (covered in the Bonus videos):
Using a MultiIndex
Merging DataFrames
Creating pivot tables
Reshaping data
Reducing memory usage
Using multiple aggregation functions
Resampling datetime columns
Profiling a DataFrame
Styling a DataFrame
Join 2,000+ happy students...
Fred C.
Clear, concise, incredibly easy to follow. Your explanations were exactly what I was looking for.
E. B. (Senior Data Scientist)
The best video lecture series that I have found. I love how you explain what is going on behind-the-scenes rather than just showing how to write the code.
Fred Tsang
This is not just a laundry list of "how to" items, but the fundamentals of how to effectively use pandas.
Rohit Jacob
Being a big user of R, your tutorials have made me like Python so much that I have completely switched to Python at work.
D. K.
What separates you is your ability to explain complicated concepts in plain English so I don’t feel like I accidentally walked into a graduate level programming course.
N. D.
I can say without hesitation that you provide the best resources for pandas I have ever used.
F. M.
I particularly liked that you didn't just present syntax, you gave reasons why the syntax is the way it is. And when you understand that, you don't need to commit half as much stuff to memory.
Nathaniel K.
Your videos were absolutely crucial in helping me understand pandas well enough to take advantage of it for my senior project.
Thank you so very, very much - I may not have completed my project and graduated without your help!
O. H.
Your patience to explain the "why" underneath each concept makes all the difference. I have previously taken courses on Coursera and similar sites and the quality of your teaching is far superior to the rest.
Gabi Turner
Your videos are absolutely awesome, you are the first online resource on pandas I can easily follow.
C. C.
I had to make a tool for work using pandas and I wouldn't have been able to do it without your help. You're honestly one of the best YouTube code teachers.
Tom Skinner
Perfectly paced, clear, succinct. It was just what I needed.
Aren't these videos already on YouTube?
Since 2016, these videos have gotten more than 4.5 million views on YouTube.
In 2025, I still believe these videos are the single best way to learn the fundamentals of pandas.
Here's why you'll have a better learning experience on my platform:
No ads
Save your progress in the course
Download the course notebooks (updated in 2024 with pandas 2.1.4)
Detailed notes below each video about changes in pandas
30 exercises to practice everything you're learning
Post a question and I'll do my best to respond
Free certificate of completion at the end of the course
I'm a Statistician and have been using SAS for over 35 years. Recently I started working in a company that uses pandas for analytics and I had to be up to speed with the new environment.
I found Kevin’s lectures concise, clear and with the right amount of information. Highly recommend to anyone who is new to pandas or wants to refresh their skills.
- Raimundo Gomes
FAQs
What do I need to know before the course?
You don't need to have any experience with pandas.
You do need to know how to write basic Python code. If you're new to Python, I recommend enrolling in Python Essentials for Data Scientists first.
What software do I need to install?
If you want to code along with me, you'll need to install pandas, matplotlib, and their dependencies.
You can use any code editor you like, though I'll be using the Jupyter notebook.
The easiest way to install these libraries (plus Jupyter) is by installing the free Anaconda distribution. Or, you can follow the advanced installation instructions.
Alternatively, you could use Google Colab. Colab is free, runs entirely in your browser, provides you with a Jupyter-like interface, and includes both pandas and matplotlib.
What software versions do I need?
I updated the course notebooks in 2024 using pandas 2.1.4, but they should work well with any recent version of pandas.
I recorded most of the videos using pandas 0.18, so there will be some differences between the notebooks and the videos. However, below each video I explain any changes I made to the code.
How long is the course?
The 30 course videos total 6 hours (~12 minutes per video), and the 4 bonus videos total 1.5 hours (~25 minutes per video).
In addition, there are 30 optional exercises to practice what you're learning, and those are each designed to take 10 minutes or less.
What if I need help during the course?
How do I earn a certificate of completion?
Once you have watched all of the videos and attempted all of the exercises, you can request a free certificate of completion.
How long will I have access to the course?
You will have lifetime access to the videos, exercises, notebooks, and datasets.
Course Outline
Introduction
Course videos
Bonus videos
Conclusion
This may be the clearest, most practical, and straightforward Python tutorial I've watched to date. Fantastic job and THANK YOU.
- Brian Kays
👋 Welcome to Data School!
My name is Kevin, and I've taught Data Science in Python to over a million students.
My courses explain data science topics in a clear, thorough, and step-by-step manner.
I'd love to teach you, regardless of your educational background or professional experience.
Thanks for joining me! 🙌