What are the use cases for this prompt?

This prompt can be used for: Identify and handle outliers.

What is the difficulty level and which AI tool should I use?

This prompt is beginner level. It works with all AI tools (ChatGPT, Claude, Gemini, etc.).

📊Analyse de donnéesBeginnerAll AIs

Detect outliers

Identify and handle outliers

Paste in your AI

Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.

Write Python code to detect outliers in the numerical columns of DataFrame df using three methods: IQR method, Z-score (threshold=3), and Isolation Forest. Compare results, visualize outliers with box plots, and recommend which method is most appropriate for [describe data distribution].

Personalize this prompt with Léa

Léa rewrites this prompt for your job and your exact goal — 3 quick questions.

Use Cases

Identify and handle outliers

Improve this prompt

Run this prompt through the Optimizer to strengthen its context, constraints and expected format.

Improve this prompt with the Optimizer

Comments

LéaAI
💡 Astuce : Pour choisir la méthode, testez d'abord la normalité (ex : test de Shapiro). Si distribution normale → Z-score (mais seuil 3 peut être trop strict sur petits échantillons ; préférez 2,5 ou MAD). Si asymétrique ou avec outliers nombreux → IQR (plus robuste). Pour données volumineuses ou non linéaires → Isolation Forest.