alteryx/evalml

Improve implementation of ``NullDataCheck``

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#3,273 opened on Jan 22, 2022

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 (1 comment) (0 reactions) (1 assignee)Python (93 forks)auto 404
good first issueperformancerefactor

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Description

Follow up on https://github.com/alteryx/evalml/pull/3182 based on @freddyaboulton's comment:

I think we can improve this implementation. Right now we do two scans of the data to determine the highly null columns and the columns with any nulls. Doing so also involves creating a new copy of the data without NaturalLanguage/DateTime.

I think if we refactor get_null_column_information to return {col_name: % nulls} we only have to do one scan without creating another copy to determine which are highly null and which are null.

Originally posted by @freddyaboulton in https://github.com/alteryx/evalml/pull/3182#discussion_r789977564

Contributor guide

Research direction
Refactor the `get null column information` function to return a dictionary mapping column names to their null percentage. This will eliminate the need for two scans and a copy of the data. Ensure the updated `NullDataCheck` uses this single dictionary to identify highly null columns and columns with any nulls.
Tech stack
python
Domain
datamachine learning
Issue type
Refactor
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
Python
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
75