--- description: Anaconda : avantages et inconvénients. Lisez les avis clients, consultez les prix et découvrez les fonctionnalités. image: https://gdm-localsites-assets-gfprod.imgix.net/images/capterra/og_logo-e5a8c001ed0bd1bb922639230fcea71a.png?auto=format%2Cenhance%2Ccompress title: Anaconda - Avis, notes, prix et abonnements - Capterra Canada 2026 --- Breadcrumb: [Accueil](/) > [Outils d'apprentissage automatique](/directory/31103/machine-learning/software) > [Anaconda](/software/191760/anaconda) # Anaconda Canonical: https://fr.capterra.ca/software/191760/anaconda Page : 1/5\ Suivant: [Page suivante](https://fr.capterra.ca/software/191760/anaconda?page=2) > Anaconda est une plateforme de science des données open source populaire pour Python qui facilite l'analyse de données. > > Conclusion : 86 utilisateurs lui ont donné la note de **4.6/5**. Figure au meilleur classement pour **Probabilité de recommander le produit**. ----- ## Présentation ### Qui utilise Anaconda? Les professionnels de la science des données, les entreprises axées sur les données, et les communautés open source. ## Statistiques et notes | Métrique | Notation | En détail | | **Note globale** | **4.6/5** | 86 Avis | | Simplicité | 4.4/5 | D'après l'ensemble des avis | | Support client | 4.0/5 | D'après l'ensemble des avis | | Rapport qualité-prix | 4.6/5 | D'après l'ensemble des avis | | Fonctionnalités | 4.7/5 | D'après l'ensemble des avis | | Pourcentage de recommandation | 90% | (9/10 Probabilité de recommander le produit) | ## À propos du vendeur - **Entreprise**: Anaconda ## Contexte commercial - **Type de licence**: (Version gratuite disponible) (Version d’essai gratuite) - **Public cible**: Travailleur autonome, 2–10, 11–50, 51–200, 201–500, 501–1 000, 1 001–5 000, 5 001–10 000, 10 000+ - **Déploiement et plateformes**: Mac (ordinateur), Windows (ordinateur), Linux (ordinateur) - **Langues**: anglais - **Pays disponibles**: Canada, Royaume-Uni, États-Unis ## Fonctionnalités - API - Analyse prédictive - Analyse statistique - Analyse visuelle - Bibliothèque d'algorithmes de ML - Connecteurs de données - Contrôles/Permissions d'accès - Data discovery - Deep learning - Extraction de données - Gouvernance de l'information - Importation et exportation de données - Logiciels de chatbots - Modèle de formation - Modélisation prédictive - Outils de collaboration - Rapports et analyses - Saisie et transfert de données - Sources de données multiples - Suivi des indicateurs clés de performance - Sécurité des données - Tableau de bord - Traitement automatique du langage naturel - Traitement des gros volumes - Visualisation - Visualisation de données ## Ressources d'aide - Base de connaissances ## Category - [Outils d'apprentissage automatique](https://fr.capterra.ca/directory/31103/machine-learning/software) ## Catégories connexes - [Outils d'apprentissage automatique](https://fr.capterra.ca/directory/31103/machine-learning/software) - [Outils de big data](https://fr.capterra.ca/directory/30851/big-data/software) - [Outils de tableaux de bord](https://fr.capterra.ca/directory/30839/dashboard/software) - [Logiciels d'intelligence artificielle](https://fr.capterra.ca/directory/30938/artificial-intelligence/software) - [Logiciels de gestion des données](https://fr.capterra.ca/directory/31003/data-management/software) ## Logiciels similaires 1. [Google Cloud](https://fr.capterra.ca/software/170983/google-cloud-platform) — 4.7/5 (2262 reviews) 2. [Rayven](https://fr.capterra.ca/software/173908/rayven-industrial-business-intelligence) — 5.0/5 (24 reviews) 3. [Clickworker](https://fr.capterra.ca/software/175432/clickworker) — 4.3/5 (58 reviews) 4. [XLSTAT](https://fr.capterra.ca/software/119448/xlstat) — 4.7/5 (398 reviews) 5. [MySQL](https://fr.capterra.ca/software/11482/mysql) — 4.6/5 (2094 reviews) ## Avis ### "Easy to setup environments and code in many languages with Anaconda. Can be integrated with Streamlit." — 5.0/5 > **Fungai Nicole** | *18 avril 2025* | Hôpitaux et soins de santé | Taux de recommandation : 9.0/10 > > **Avantages**: I liked how easy it was to integrate the Anaconda environment with Streamlit. I was having trouble installing Streamlit on my computer and as soon I followed the easy instructions, I could just play a Play button and the environment would run smoothly. > > **Inconvénients**: The Windows setup file can take a while to download but it is worth it. > > I loved integrating Anaconda with Streamlit. I had spent a significant amount of time trying to setup Streamlit on my PC but it was not running. I like that it has a large variety of integrations for example CoLab and this was really awesome because I could edit my python code in the Anaconda interface before deploying my finished app to Streamlit. You can use a lot of coding languages to code from C to others like visual basic. ----- ### "must use for every data scientist" — 5.0/5 > **Terry** | *3 mai 2025* | Exploitation minière et métaux | Taux de recommandation : 10.0/10 > > **Avantages**: best package management solution for python, two IDE can choose from jupyter or spyder > > **Inconvénients**: conda managed packages are usually lagging actual package versions, using pip install can easily create conflicts ----- ### "Review of Anaconda" — 3.0/5 > **Christhian** | *21 octobre 2024* | Services financiers | Taux de recommandation : 9.0/10 > > **Avantages**: As a data scientist, we all know and have use anaconda because it provide every element needed to help us develop our projet. Between those elements we have IDEs, notebook editor, Python and R preinstalled with the most used libraries. > > **Inconvénients**: Anaconda unfortunately takes too much space on laptop and it is sometimes really slow even when opening it ----- ### "A convenient and beginner friendly tool for managing data science workflows" — 5.0/5 > **Aditya** | *4 janvier 2026* | Réseaux informatiques | Taux de recommandation : 8.0/10 > > **Avantages**: What I liked most about Anaconda is how smoothly it brings everything together in one place. Installing Python, managing libraries, and working with tools like Jupyter Notebook becomes much simpler, especially when handling data analysis tasks. It saves time, reduces setup issues, and lets me focus more on learning and building projects rather than fixing environment problems. > > **Inconvénients**: One thing I liked least about Anaconda is that it can feel heavy and slow at times, especially on systems with limited resources. The environment management, while powerful, can be confusing in the beginning and sometimes leads to version conflicts. Also, updates and package installations occasionally take longer than expected, which can interrupt workflow. > > Overall, my experience with Anaconda has been positive. It has made data management much easier by providing a stable environment to work with large datasets and popular libraries without constant dependency issues. The free version offers a lot, especially for students and individual users, which makes it very cost-effective. ----- ### "Data Science platform with extensive functionality and ease of version management" — 5.0/5 > **Ferhat** | *25 janvier 2020* | Services et technologies de l'information | Taux de recommandation : 9.0/10 > > **Avantages**: I loved that: - Almost all libraries come default with Anaconda, such as Pandas, NumPy, Matplotlib, Seaborn, Sci-kit Learn. - Even the libraries that does not come default in Anaconda can be easily installed via Anaconda user interface because the namespace contains such information. For example XGBoost, CatBoost, LightGBM, Imbalanced-learn, tsfresh libraries can be installed easily with no need to pip or other command-line interface command. - Maintenance and update of installed libraries are managed easily and automatically in Anaconda. You can see your installed library's current version and if there's any update, it automatically checks and notify you so that you can update them all with one click only. - Anaconda comes with platforms such as Jupyter Notebook, Spyder, Orange, VSCode and more. So you can develop your Python/R script in any of those according to your preference. > > **Inconvénients**: There are two drawbacks I have seen so far: - As more and more libraries are installed, Anaconda opening becomes slower. - Update of libraries at once is relatively slow but I guess that's understandable, comparing it to all the labor otherwise that would be carried out by the developer. > > I love Anaconda overall thanks to its extensive set of features, platforms it contains and ability to manage installed libraries and install new ones. Version management is very critical for a developer. For example, I recently needed a function that was brought to Pandas just recently, which was 'Int64' datatype that enabled NaN values for Int datatype in DataFrame. I realized I needed to update Pandas. Rather than going through painful process of library update and management, I have gone through this process with ease. ----- Page : 1/5\ Suivant: [Page suivante](https://fr.capterra.ca/software/191760/anaconda?page=2) ## Liens - [Afficher sur Capterra](https://fr.capterra.ca/software/191760/anaconda) ## Cette page est disponible dans les langues suivantes. | Langue | URL | | de | | | de-AT | | | de-CH | | | en | | | en-AE | | | en-AU | | | en-CA | | | en-GB | | | en-IE | | | en-IL | | | en-IN | | | en-NZ | | | en-SG | | | en-ZA | | | fr | | | fr-BE | | | fr-CA | | | fr-LU | | | it | | ----- ## Données structurées