One Hot Encoder with Python Machine Learning (Scikit-Learn)

In this Python Machine Learning Tutorial, we take a look at how you can change categorical data to numeric with the help of One Hot Encoder

Interested in discussing a Data or AI project? Feel free to reach out via email or simply complete the contact form on my website.

🍿 WATCH NEXT

MY OTHER SOCIALS:

WHO AM I?
As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.

This YouTube channel serves as both a platform for sharing knowledge and a personal journey of continuous learning. With a commitment to growth, I aim to expand my skill set by publishing 2 to 3 new videos each week, delving into various aspects of data analytics/science and Artificial Intelligence. Join me on this exciting journey as we explore the endless possibilities of data together.

*This is an affiliate program. I may receive a small portion of the final sale at no extra cost to you.

[RyanAndMattDataScience]

Hey guys I hope you enjoyed the video! If you did please subscribe to the channel!


*Both Datacamp and Stratascratch are affiliate links.

[aniketshrikondawar]

Please make sure all cells are visible on screen. Sometimes not able to view end of cell content.

[omer]

thanks a lot dude! really helped me grasp the basics!

[ahsanjamil]

in case if we have multiple variables which are non-ordinal, do we use the onehotencoder on all the variables at once by adding them to the list initially or do we do this one by one?

[RyanAndMattDataScience]

Have a need for a data project? Email me or fill out the form on my website.

[Futureyouth-bebo]

dude how about if i have two different datasets while theier categorical values are different how can i do one hot encoding
the first one has 9349 rows × 17 columns
and the second one has 365 rows × 17 columns while if i make one hot encoding they will be produced
for the first one they become 611 columns of hot encoding
and the second one become 20 columns please help me how can i do this note the two datasets have Origin and destintion city names

[alonzoslim]

This is a great video. Explained in a manner that a newbie like myself can understand. Thank you.

A question: What if the dataset contains multiple categorical variables (as well as numerical), and they are all required as input to make a prediction. How can one go about it?

[shivi_was_never_here]

Thanks a lot Ryan! This has to be one of the best videos out here dealing with encoders. If only others were this easy!
Thanks again.

[juanDoAs]

Trying your code I get this error: 'AttributeError: 'OneHotEncoder' object has no attribute 'set_output''. Any idea why this is?

[PhilTag-mlwd]

Stopped a bit short. Need to go through how to use the encoder for predicting and not just setting up for training. eg. enc.transform() on the features you need to run the prediction on . Has been a bit of a pain with the datatype.

[message]

Thanks a lot was a great help :) hope you have a good day