Encoding Categories
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What is Encoding Categories?
Categorical encoding converts text category labels into numerical values that machine learning algorithms can process. Common approaches include label encoding (assigning each category an integer), one-hot encoding (creating binary columns for each category with pd.get_dummies()), and ordinal encoding for ordered categories.
Free resources to learn Encoding Categories
- Official docsCategorical data
- ArticleEncoding Categorical Variables: One-hot vs Dummy Encoding
More in stage 10: Exploratory Data Analysis
Encoding Categories: common questions
Can I learn Encoding Categories in Hindi?
This lesson is written in English. Once you sign in, open it in the interactive course and ask the AI tutor to explain Encoding Categories in Hindi or Hinglish. The tutor answers from this lesson’s own text, so it stays on the syllabus, and it runs on your own Google, OpenAI or Anthropic key.
Is this Encoding Categories tutorial for beginners?
It is lesson 76 of 112 in the free Python for Data Analysis roadmap, in stage 10, Exploratory Data Analysis. If you are new to Python for Data Analysis, start from stage 1 and come back here in order; if you already know the earlier stages, this lesson stands on its own.