-
Notifications
You must be signed in to change notification settings - Fork 87
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Allow user to filter which features to encode for OneHotEncoder #1249
Conversation
Codecov Report
@@ Coverage Diff @@
## main #1249 +/- ##
=======================================
Coverage 99.93% 99.93%
=======================================
Files 207 207
Lines 12997 13031 +34
=======================================
+ Hits 12988 13022 +34
Misses 9 9
Continue to review full report at Codecov.
|
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
@angela97lin I think this is great! Right now, we fit and transform on different columns which can cause bugs. I'm a fan of letting users fit/transform on the columns they pass in as features_to_encode
to get around this but open to other solutions.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
@angela97lin Thanks this looks great!
Closes #1237.
I chose to raise a ValueError if any column in
features_to_encode
does not exist in the input DataFrame.