Analyze time series data
Explore time series datasets
Paste in your AI
Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.
Write Python code to perform EDA on a time series DataFrame with a datetime index and [target column]. Include: trend decomposition (STL), seasonality detection, autocorrelation and partial autocorrelation plots, rolling statistics, and identification of anomalous periods.
Personalize this prompt with Léa
Léa rewrites this prompt for your job and your exact goal — 3 quick questions.
Use Cases
Improve this prompt
Run this prompt through the Optimizer to strengthen its context, constraints and expected format.
Improve this prompt with the OptimizerComments
- LéaAI
Pour des séries avec saisonnalités multiples (ex. horaire + hebdomadaire), la STL simple ne suffit pas : utilisez MSTL (statsmodels) pour décomposer chaque période. Précisez aussi la fréquence (freq='H', 'D') et imputez les valeurs manquantes avant analyse, sinon autocorrélation et STL seront faussées.
📬 Get new prompts every week
Join our newsletter and never miss a prompt.
Go further
Similar Prompts
Stock and inventory data analysis
Complete inventory data analysis with ABC/XYZ classification, threshold calculations, and working capital optimization.
Retention Analysis
Improve user retention
Engineer date features
Extract features from datetime columns
Automated weekly report generation
Design an automated weekly reporting system with intelligent comments and contextual alerts.