Join us and get access to hundreds of tutorials and a community of expert Pythonistas.

Unlock This Lesson

This lesson is for members only. Join us and get access to hundreds of tutorials and a community of expert Pythonistas.

Unlock This Lesson

Hint: You can adjust the default video playback speed in your account settings.
Hint: You can set the default subtitles language in your account settings.
Sorry! Looks like there’s an issue with video playback 🙁 This might be due to a temporary outage or because of a configuration issue with your browser. Please see our video player troubleshooting guide to resolve the issue.

The Pandas DataFrame (Summary)

You now know what a pandas DataFrame is, what some of its features are, and how you can use it to work with data efficiently. pandas DataFrames are powerful, user-friendly data structures that you can use to gain deeper insight into your datasets!

In this course, you’ve learned:

  • What a pandas DataFrame is and how to create one
  • How to access, modify, add, sort, filter, and delete data
  • How to use NumPy routines with DataFrames
  • How to handle missing values
  • How to work with time-series data
  • How to visualize data contained in DataFrames

For more information about topics covered in this course, please take a look at the following resources:


Sample Code (.zip)

39.9 KB


Course Slides (.pdf)

1.9 MB

00:00 So, you’ve made it to the end! I hope that you learned a lot and you see now how maybe you can use pandas to solve some of the problems that you’re working on that have to do with spreadsheets or tabular data in general. Let’s go over real quick some of the things that you learned.

00:15 You learned what a pandas DataFrame is and how to create one. We worked on how to access and modify, add, sort, filter, and delete data from a DataFrame.

00:26 We talked about how to handle missing values in a DataFrame. We worked a bit with time-series data, and we saw how to quickly visualize data in a DataFrame.

00:37 So, what now? Well, keep learning! Take what you’ve learned and dive deeper into the workings of pandas. Go over to the search field and look up pandas.

00:49 Here are a few courses that you might find. There’s a great course on the .groupby() method that is frequently used with pandas DataFrames. A lot of times with DataFrames, you want to group data by a certain criteria and then apply some sort of aggregate function to each of the groups. We did a little bit of this when we were looking at the .resample() method.

01:11 If you’re a project-based learner, then I highly recommend Pandas Project: Make a Gradebook it’s available both as a tutorial and a video course.

01:21 And then once you’ve learned some of the basics of pandas, then definitely check out the tricks and features you may not know to take your understanding of the pandas module to a whole new level. All right, until next time! I’m Cesar Aguilar.

aniketbarphe on Sept. 8, 2021

Excellent Course! 10 Star out of 10 Star. Recommended to Everyone!

Become a Member to join the conversation.