인프런 커뮤니티 질문&답변
작성한 질문수
답변 7
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Common Technical Contexts
Data Binning (Categorization): In data science or analytics (often using Python/Pandas or SQL), it is commonly used as a column header or variable name for age segmentation. For example, converting raw ages (like 25, 42, 60) into predefined buckets (like "Young Adult," "Middle Age," "Senior") to simplify analysis.
Database Schema Update: It could represent a new field added to a database table to store updated age category information for users, distinguishing it from an old
age_groupcolumn.Business Logic/Algorithms: In software engineering, this might be a variable used in a function that recalculates a user's age category (e.g., when a user has a birthday and moves into a new demographic tier).
greate!play <a href='https://aivideomaker.ai'>AI Video Maker</a>
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Common Technical Contexts
Data Binning (Categorization): In data science or analytics (often using Python/Pandas or SQL), it is commonly used as a column header or variable name for age segmentation. For example, converting raw ages (like 25, 42, 60) into predefined buckets (like "Young Adult," "Middle Age," "Senior") to simplify analysis.
Database Schema Update: It could represent a new field added to a database table to store updated age category information for users, distinguishing it from an old
age_groupcolumn.Business Logic/Algorithms: In software engineering, this might be a variable used in a function that recalculates a user's age category (e.g., when a user has a birthday and moves into a new demographic tier).
greate!play <a href='https://aivideomaker.ai'>AI Video Maker</a>
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@basketball legends It is an issue that you should not be concerned about if you look at it based on the third test. If you listen to the lecture correctly, it will be explained to you, but if you don't listen to the lecture as I do and just solve the problem, you will not be able to understand it.