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
Limiting fraud dataset to speed up doc builds #1646
Conversation
Codecov Report
@@ Coverage Diff @@
## main #1646 +/- ##
=======================================
Coverage 100.0% 100.0%
=======================================
Files 240 240
Lines 18270 18270
=======================================
Hits 18262 18262
Misses 8 8 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.
Thanks @bchen1116 !!
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.
Thanks!
@@ -58,7 +58,7 @@ | |||
"source": [ | |||
"import evalml\n", | |||
"from evalml.utils import infer_feature_types\n", | |||
"X, y = evalml.demos.load_fraud(return_pandas=True)\n", | |||
"X, y = evalml.demos.load_fraud(n_rows=1000, return_pandas=True)\n", |
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.
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.
LGTM!
Testing to see whether or not limiting the fraud dataset will cause the doc builds to pass
Notebook builds passed here and here, and doc example is here