The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.
With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages.
Analytics Analyst at a tech services company with 10,001+ employees
Real User
2020-08-13T08:33:00Z
Aug 13, 2020
It's interesting. It's user friendly. That's what makes it outstanding among the others.
It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science.
Anaconda makes it easy for you to install and maintain Python environments. Our development team tests to ensure compatibility of Python packages in Anaconda. We support and provide open source assurance for packages in Anaconda to mitigate your risk in using open source and meet your regulatory compliance requirements.Python is the fastest growing language for data science. Anaconda includes 720+ Python open source packages and now includes essential R packages. This powerful combination...
The tool's most valuable feature is its cloud-based nature, allowing accessibility from anywhere. Additionally, using Jupyter Notebook makes it easy to handle bugs and errors.
I can use Anaconda for non-heavy tasks.
With Anaconda Navigator, we have been able to use multiple IDEs such as JupyterLab, Jupyter Notebook, Spyder, Visual Studio Code, and RStudio in one place. The platform-agnostic package manager, "Conda", makes life easy when it comes to managing and installing packages.
The documentation is excellent and the solution has a very large and active community that supports it.
It's interesting. It's user friendly. That's what makes it outstanding among the others.
It has a collection of R, Python, and others. Their platform strategy has a collection of many other visualization tools, apart from Spyder and RStudio, which is really helpful for data science. For any data science professional, Anaconda is really handy. It has almost all the tools for data science.
The product is responsive, sleek and has a beautiful interface that is pleasant to use. It helps users to easily share code.
The virtual environment is very good.
The most valuable feature is the Jupyter notebook that allows us to write the Python code, compile it on the fly, and then look at the results.
The solution is stable.
The most valuable feature is the set of libraries that are used to support the functionality that we require.
The most advantageous feature is the logic building.
The notebook feature is an improvement over RStudio.
The best part of Anaconda is the media distribution that comes as part of it. It gets us started very quickly.
It helped us find find the optimal area for where our warehouse should be located.