Classification using Pandas and Scikit-Learn 

here´s the link from the talk: github.com/jseabold/depy

This is the best intro to Pandas/Scikit-Learn video I've come across. I have one question, why use the "mean_absolute_error" to access accuracy? Isn't that a metric for scoring a regression model rather than a classification model?

This is a great overview of sklearn and pandas! THANKS!

:O Until now, I was thinking that sklearn does not support dataframes and I was (painfully sometimes) transforming them to arrays!!! Very informative video!!!

From 0 to 60 with Pandas in 45 minutes... Very nice!

Thanks for posting this. There was a lot to process, so I've downloaded your notebook.

Thanks for posting this.Getting error like " ValueError: could not convert string to float: '>50K'" while running metrics.mean_absolute_error(y_test, dtree.predict(X_test)) . How to dubug?

Very informative video, but can anybody reply me where do you run this line to generate image of decision tree dot -Tpng tree.dot -o tree.png i am in window and i tried to run in command prompt i tried by giving python full path too, i got error like global variable dot_parser is not defined , but i have installed pydot and dot_parser too I would be happy if anyone can help me to convert the dot file to png file

Why is there a link to the same video on another site, but no link for the github repository?!! Please post the link for the repository

Materials: github.com/jseabold/depy

Thanks a lot. This is the best one if anyone needs to learn about classification!!

This is a very nice video! Demonstrates the power of Pandas

awesome talk

great talk.