We may earn an affiliate commission when you visit our partners.

Nettoyer vos données avec Python

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.

Enroll now

Or subscribe to Coursera Plus

And get unlimited access to Coursera

Three deals to help you save

We found three deals and offers that may be relevant to this course.

Save money when you learn. All coupon codes, vouchers, and discounts are applied automatically unless otherwise noted.

Valid until December 12

Annual Subscription Savings

Unlock programs from Google, Microsoft, and IBM and join 77% of learners who reported positive career outcomes.

Only $239!

Valid for a limited time only

Future-proof your career

Access O'Reilly books, live events, courses, and more. Save with an annual subscription.

Take

15%

off

What's inside

Syllabus

Project Overview

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Vous donne les connaissances et les outils pour charger, nettoyer et explorer des données alimentaires à partir de sources ouvertes

Approfondit la manipulation et l'analyse de données en Python

Développe des compétences en matière de traitement des données manquantes

Save this course

Save Nettoyer vos données avec Python to your list so you can find it easily later:

Save

Reviews summary

Jupyter for python data cleaning

This course is a 5-star rated data cleaning course that uses Jupyter notebooks and Python. Students found the course to be clear and well-taught.

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Nettoyer vos données avec Python with these activities:

Review basics of Jupyter

Show steps

Familiarize yourself with the Jupyter environment to make the most of the course.

Browse courses on Jupyter

Show steps

Review the Jupyter Notebook interface and basic commands.
Practice loading a sample dataset into a Jupyter Notebook.
Execute basic data manipulation commands in Jupyter.

Participate in a study group

Show steps

Enhance understanding through collaborative learning and discussions.

Show steps

Form a study group with classmates.
Meet regularly to discuss course materials and assignments.
Share knowledge and insights with peers.

Practice data cleaning techniques

Show steps

Improve your data cleaning skills through repetitive exercises.

Browse courses on Data Cleaning

Show steps

Identify and remove duplicate rows.
Handle missing values using Pandas and missingno library.
Clean data based on business rules and statistical techniques.

Four other activities

Expand to see all activities and additional details

Show all seven activities

Attend a data science workshop

Show steps

Enhance your data science knowledge and skills through structured workshops.

Browse courses on Data Science

Show steps

Identify relevant workshops and attend them.
Participate actively in discussions and exercises.
Apply workshop learnings to your coursework.

Explore advanced data visualization techniques

Show steps

Expand your data visualization capabilities by following guided tutorials.

Browse courses on Data Visualization

Show steps

Create interactive data visualizations using SeaBorn.
Generate complex plots using Matplotlib.
Explore advanced visualization techniques.

Develop a data analysis report

Show steps

Demonstrate your data analysis skills by creating a comprehensive report.

Browse courses on Data Analysis

Show steps

Define the problem and research question.
Analyze the data using appropriate techniques.
Develop insights and conclusions.
Communicate findings effectively in a written report.

Contribute to an open-source data science project

Show steps

Gain practical experience by contributing to the data science community.

Browse courses on Open Source

Show steps

Identify suitable open-source data science projects.
Explore the codebase and understand the project's goals.
Make meaningful contributions to the project.

Career center

Learners who complete Nettoyer vos données avec Python will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist is responsible for collecting, cleaning, analyzing data, and presenting actionable insights to make informed decisions. This course would help build a foundation in data cleaning techniques, which is a critical skill for Data Scientists. The course also covers data exploration and visualization, which are essential for presenting insights effectively.

See salaries and explore the career path for Data Scientist

Data Analyst

A Data Analyst is responsible for gathering, cleaning, and analyzing data to identify trends and patterns. This course would provide a strong foundation in data cleaning techniques, which is essential for Data Analysts. The course also covers data exploration and visualization, which are important skills for presenting insights.

See salaries and explore the career path for Data Analyst

Business Analyst

A Business Analyst is responsible for analyzing business processes and identifying areas for improvement. This course would provide a foundation in data cleaning techniques, which can be useful for Business Analysts who need to clean data for analysis. The course also covers data exploration and visualization, which can be helpful for presenting insights to stakeholders.

See salaries and explore the career path for Business Analyst

Statistician

A Statistician is responsible for collecting, analyzing, and interpreting data to make informed decisions. This course would provide a foundation in data cleaning techniques, which is essential for Statisticians. The course also covers data exploration and visualization, which are important skills for presenting insights.

See salaries and explore the career path for Statistician

Software Engineer

A Software Engineer is responsible for designing, developing, and maintaining software applications. This course would provide a foundation in data cleaning techniques, which can be helpful for Software Engineers who need to clean data for analysis or integration. The course also covers data exploration and visualization, which can be useful for debugging and testing software.

See salaries and explore the career path for Software Engineer

Data Engineer

A Data Engineer is responsible for building and maintaining data pipelines and infrastructure. This course would provide a foundation in data cleaning techniques, which is essential for Data Engineers. The course also covers data exploration and visualization, which can be useful for understanding data and designing data pipelines.

See salaries and explore the career path for Data Engineer

Product Manager

A Product Manager is responsible for managing the development and launch of new products. This course may be useful for Product Managers who need to understand data cleaning techniques for product development and market research.

See salaries and explore the career path for Product Manager

Marketing Analyst

A Marketing Analyst is responsible for analyzing marketing data to identify trends and opportunities. This course may be useful for Marketing Analysts who need to understand data cleaning techniques for data analysis and reporting.

See salaries and explore the career path for Marketing Analyst

Financial Analyst

A Financial Analyst is responsible for analyzing financial data to make investment recommendations. This course may be useful for Financial Analysts who need to understand data cleaning techniques for data analysis and reporting.

See salaries and explore the career path for Financial Analyst

Operations Manager

An Operations Manager is responsible for overseeing the day-to-day operations of a business. This course may be useful for Operations Managers who need to understand data cleaning techniques for data analysis and process improvement.

See salaries and explore the career path for Operations Manager

Customer Success Manager

A Customer Success Manager is responsible for ensuring that customers are satisfied with a company's products or services. This course may be useful for Customer Success Managers who need to understand data cleaning techniques for data analysis and customer feedback.

See salaries and explore the career path for Customer Success Manager

Sales Manager

A Sales Manager is responsible for leading and managing a sales team. This course may be useful for Sales Managers who need to understand data cleaning techniques for data analysis and sales forecasting.

See salaries and explore the career path for Sales Manager

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Nettoyer vos données avec Python.

Python para análisis de datos

Save

Ce livre fournit des recettes et des exemples pratiques pour nettoyer et manipuler des données avec Pandas, la bibliothèque de manipulation de données la plus populaire de Python.

Nettoyer vos données avec Python

Three deals to help you save

What's inside

Syllabus

Good to know

Save this course

Reviews summary

Jupyter for python data cleaning

Activities

Career center

Reading list

Share

Similar courses