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What Is Anaconda?

Anaconda is a data science platform that provides tools for machine learning and artificial intelligence projects. The open-source software offers capabilities for environment management, modeling, deployment, team collaboration, and IT governance to help users take concepts from prototype to production.

Who Uses Anaconda?

Small to midsize businesses looking for open-source data science and AI tools, data scientists and ML developers, and data science teams.

Anaconda Software - 1

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Reviews of Anaconda

Average score

Overall
4.6
Ease of Use
4.4
Customer Service
4.0
Features
4.6
Value for Money
4.6

Reviews by company size (employees)

  • <50
  • 51-200
  • 201-1,000
  • >1,001

Find reviews by score

5
68%
4
29%
3
4%
Harsh
Harsh
Researcher in Spain
Verified LinkedIn User
Higher Education, 1,001–5,000 Employees
Used the Software for: 1+ year
Reviewer Source

Best tool for Python Begineers

5.0 10 months ago

Pros:

Anaconda is by far the best tool available for Python Begineers. It makes it easy to use jupyter Notebook, Jupyter Labs and other User Interfaces (UI). As compared to other UIs available like PyCharm which are paid, Anaconda is completely free and allows you do most of the tasks you would need to perform without error.

Cons:

Anaconda is bundle of many User Interfaces. As a consequence, it consumes a bit of storage space in your hard disk. Further, it may take some time to familiarize with the tool.

Edwin
Edwin
Administrative Assistant in Kenya
Verified LinkedIn User
Information Technology & Services, 11–50 Employees
Used the Software for: 1+ year
Reviewer Source

Alternatives Considered:

Best software for developing projects from different fields.

4.0 3 years ago

Comments: This software has enabled me learn many things from different fields with different languages most especially python programming. Indeed this software includes many packages on one software and this has made my work more effective and efficient than ever.

Pros:

First is its broad support for python libraries. This software includes various important libraries therefore it does not limit a programmer from using it either in python or R programming. It is an important software for developing long term projects that can run in different python versions. It was hard at first for me to select the best software to learn machine learning but since I got anaconda machine learning has been easy. Runs on more than one platform or operating system. Lastly installing new libraries on anaconda is so easy since it doesn't requires different steps for you to install those libraries.

Cons:

This software takes a long time to open compared to other related alternatives. When I try to update one package of anaconda, it automatically updates all the packages and this I don't like. I don't have many negative things since it covers all my expectations only that if you are using Jupyter Notebook your internet connectivity should be good.

abir
Trainer in Poland
Professional Training & Coaching, 11–50 Employees
Used the Software for: 1+ year
Reviewer Source

Python distribution

3.0 2 months ago

Pros:

It contains almost all the python IDE. Once we download Anaconda all the most needed libraries are already installed.

Cons:

When I installed Numpy and Pandas libraries they weren't working on "Pycharm" even when they were working in "VS Code"

Ferhat
Data Warehouse Developer in Türkiye
Information Technology & Services, 5,001–10,000 Employees
Used the Software for: 2+ years
Reviewer Source

Alternatives Considered:

Data Science platform with extensive functionality and ease of version management

5.0 4 years ago

Comments: 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.

Pros:

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.

Cons:

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.

Yigit
Engineer in Türkiye
Consumer Electronics, 10,000+ Employees
Used the Software for: 1+ year
Reviewer Source

Better alternative for Numeric analysis and visualization

5.0 4 years ago

Comments: Anaconda is very useful tool with many great open source tools that come with it, such as Pandas, NumPy, SciPy, Matplotlib, Seaborn as well as convenience to keep them updated, and install new ones.

Pros:

I liked that it comes with a lot of ready to use libraries out of package, such as NumPy, Pandas, SciPy, Matplotlib and Seaborn, which makes it possible to read, process, model and visualize the data. I liked that version management is very easy to handle, too. It is possible to simply click on the library and then "install/update" button below. It is also very easy to install new ones, its default namespace already contains many many Python libraries and you can filter them using "not installed ones". Then again, to install, you simply click on the checkboxes.

Cons:

The only drawback I can say is its rapidity is a bit low. I guess that's expected considering the number of packages it comes with, and adding new ones to these ones. Another strange thing I came across is, whenever I want to update a package that was already installed, instead of updating that one only, it updated them all, which is odd and very time consuming, considered each update takes some significant time.