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.

Explore Your Dataset With Pandas (Summary)

In this course, you’ve learned how to start exploring a dataset with the Pandas Python library. You saw how you could access specific rows and columns to manage even the largest of datasets. You’ve also seen multiple techniques to prepare and clean your data, by specifying the data type of columns, dealing with missing values, and more. You’ve even created queries, aggregations, and plots based on those.

Now you can:

  • Work with Series and DataFrame objects
  • Subset your data with .loc, .iloc, and the indexing operator
  • Answer questions with queries, grouping, and aggregation
  • Handle missing, invalid, and inconsistent data
  • Visualize your dataset in a Jupyter Notebook

You can further develop these skills with Fast, Flexible, Easy and Intuitive: How to Speed Up Your Pandas Projects and Python Pandas: Tricks & Features You May Not Know. With enough practice, you will be able to tackle any datasets you find interesting and share your insights and observations with your friends and colleagues!

Download

Sample Code (.zip)

64.8 KB

Download

Course Slides (.pdf)

723.7 KB

Vijaya Kumar Marneni on June 5, 2021

I am beginner for pandas, it is quite useful to get flavour of it. I deep dive into library with this knowledge. Thank you Douglas Starnes

Become a Member to join the conversation.