--- title: Encoding Ordinal Categorical Data: Teaching Machine... description: Machine learning algorithms require numerical inputs, so categorical text data must be encoded before training. Ordinal data (e.g., Poor/Average/Good) carries... canonical: https://daily.dev/posts/encoding-ordinal-categorical-data-teaching-machine-learning-the-meaning-behind-rankings-rvxvv5gdg twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Encoding Ordinal Categorical Data: Teaching Machine Learning the Meaning Behind Rankings | daily.dev og:description: Machine learning algorithms require numerical inputs, so categorical text data must be encoded before training. Ordinal data (e.g., Poor/Average/Good) carries... og:url: https://daily.dev/posts/encoding-ordinal-categorical-data-teaching-machine-learning-the-meaning-behind-rankings-rvxvv5gdg og:image: https://api.daily.dev/og/posts/RVXVV5GdG.png og:image:alt: Encoding Ordinal Categorical Data: Teaching Machine Learning the Meaning Behind Rankings og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Encoding Ordinal Categorical Data: Teaching Machine Learning the Meaning Behind Rankings **[Medium](https://daily.dev/sources/medium_js)** · 7 min read · 0 upvotes · 0 comments ## Summary Machine learning algorithms require numerical inputs, so categorical text data must be encoded before training. Ordinal data (e.g., Poor/Average/Good) carries meaningful rankings that must be preserved during encoding. Using scikit-learn's OrdinalEncoder with explicitly defined category order converts ordered categories into ranked integers. A key mistake beginners make is relying on default alphabetical ordering, which can corrupt the ranking. The post also clarifies that LabelEncoder is for target variables only, not input features, and emphasizes fitting encoders only on training data to prevent data leakage. ColumnTransformer is recommended for real-world pipelines with mixed feature types. ## Full article daily.dev links to this article rather than hosting it. 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