![](https://storage.googleapis.com/kaggle-media/competitions/playground/cat_in_dat/cat7.jpg)
Can you find more cat in your dat?
We loved the participation and engagement with the first
[Cat in the Dat](https://www.kaggle.com/c/cat-in-the-dat)
competition.
Because this is such a common task and important skill to master, we've put together a dataset that contains
only
categorical features, and includes:
binary features
low- and high-cardinality nominal features
low- and high-cardinality  ordinal features
(potentially) cyclical features
This follow-up competition offers an even more challenging dataset so that you can continue to build your skills with the common machine learning task of encoding categorical variables.  This challenge adds the additional complexity of feature interactions, as well as missing data.
This Playground competition will give you the opportunity to try different encoding schemes for different algorithms to compare how they perform. We encourage you to share what you find with the community.
If you're not sure how to get started, you can check out the
[Categorical Variables](https://www.kaggle.com/alexisbcook/categorical-variables)
section of Kaggle's
[Intermediate Machine Learning course.](https://www.kaggle.com/learn/intermediate-machine-learning)
[Have Fun!](https://www.kaggle.com/learn/intermediate-machine-learning)