The pandas DataFrame (Summary)

The pandas DataFrame: Working With Data Efficiently Cesar Aguilar 01:35

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:

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Sample Code (.zip)

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Course Slides (.pdf)

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Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.

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 realpython.com 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.