-
-
Notifications
You must be signed in to change notification settings - Fork 18.4k
WIP: generalize categorical to N-dimensions #8012
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
Conversation
closing until I make more progress |
@@ -269,10 +269,23 @@ def __init__(self, values, levels=None, ordered=None, name=None, fastpath=False, | |||
self.levels = levels | |||
self.name = name | |||
|
|||
def _replace_codes(self, codes): |
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.
is is more used like a _constructor(...)
.
Maybe put in the |
@shoyer so you want an n-dim codes array (rather than 1-d). How would this be used? |
@jreback I expect that allowing for n-dimensional categoricals could lead to much higher performance for a DataFrame with multiple columns of the same type, in the same way that multi-dimensional arrays are positive for performance for other dtypes. e.g., you could call |
@shoyer ok, that is reasonable. And in fact right now |
No description provided.