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Nettoyer vos données avec Python

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Dans ce projet guidé, vous allez charger, nettoyer et explorer des données de produits alimentaires issues de la base de données Open Food Facts. Vous allez d’abord vous familiariser avec Jupyter, lire les données, analyser les valeurs manquantes, nettoyer les données en se basant sur les connaissances métiers mais aussi sur des techniques statistiques, vous allez ensuite remplir les valeurs manquantes. Pour réaliser cette analyse, vous allez utiliser JupyterLab avec les librairies data science en python telles que Pandas, Matplotlib, SeaBorn et missigno.

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Unlock the power of data cleaning with "Nettoyer vos données avec Python," an insightful course focused on transforming raw data into actionable insights. This beginner-level program, presented by Coursera, is designed for anyone interested in IT and Computer Science, particularly those keen on mastering data science techniques. Throughout this guided project, you'll engage with real-world food product data from the Open Food Facts database. You'll start by getting acquainted with JupyterLab and progress to reading and analyzing data, identifying and addressing missing values, and applying both domain-specific knowledge and statistical methods to clean the data effectively. The course leverages essential Python libraries, including Pandas, Matplotlib, Seaborn, and Missigno, to provide a comprehensive toolkit for data cleaning. Delivered over 120 minutes, this free course ensures an immersive learning experience, making it an ideal choice for beginners eager to develop their data science skills. Whether you're aiming to enhance your current expertise or start a new journey in data analytics, this course offers the perfect blend of theory and practical application to help you achieve your goals.