Anaconda vs. Microsoft Visual Studio

I have asked all my juniors to work with Anaconda and Pycharm only, as this is the best combination for now. Coming to use cases: 1. When you have multiple applications using multiple Python variants, it is a really good tool instead of Venv (I never like it). 2. If you have to work on multiple tools and you are someone who needs to work on data analytics, development, and machine learning, this is good. 3. If you have to work with both R and Python, then also this is a good tool, and it provides support for both.

Incentivized

It's useful for app development, debugging, and testing. I've been using it for two years and have seen it grow into a fantastic tool. All of the features, NuGet packages, and settings that enable different types of projects are fantastic. It also has a connection to Azure DevOps and Git. It's a fantastic product that's simple to use.

• Anaconda is a one-stop destination for important data science and programming tools such as Jupyter, Spider, R etc.
• Anaconda command prompt gave flexibility to use and install multiple libraries in Python easily.
• Jupyter Notebook, a famous Anaconda product is still one of the best and easy to use product for students like me out there who want to practice coding without spending too much money.

Incentivized

• Since Microsoft offers a free Community Edition of the IDE many of our new developers have used it at home or school and are very familiar with the user interface, requiring little training to move up to the paid, enterprise-friendly editions we use.
• The online community support for Visual Studio is outstanding, as solid or better than any other commercial or open-source project software.
• Microsoft continuously keeps the product up to date and has maintained a history of doing so. They use it internally for their own development so there is little chance it will ever fall out of favor and become unsupported.

Incentivized

• It can have a cloud interface to store the work.
• Compatible for large size files.
• I used R Studio for building Machine Learning models, Many times when I tried to run the entire code together the software would crash. It would lead to loss of data and changes I made.

Incentivized

• Certain settings and features can sometimes be challenging to locate. The interface isn't always intuitive.
• Sometimes there are too many ways to do the same thing. For example, users can quickly add a new workspace in Source Control Explorer when a local path shows as "Not Mapped," but it doesn't indicate that the user might want to check the dropdown list of workspaces. The shortcut of creating a new workspace by clicking on the "Not Mapped" link can lead to developers creating too many workspaces and causing workspace management to become unwieldy. If the shortcut link were removed, the user would be forced to use the Workspace dropdown. While it can add an extra step to the process, workspaces would be managed more easily, and this would enforce consistency. At the very least, there should be a high-level administrative setting to hide the shortcut link.

Incentivized

It's really good at data processing, but needs to grow more in publishing in a way that a non-programmer can interact with. It also introduces confusion for programmers that are familiar with normal Python processes which are slightly different in Anaconda such as virtualenvs.

Incentivized

VS is the best and is required for building Microsoft applications. The quality and usefulness of the product far out-weight the licensing costs associated with it.

Incentivized

I am giving this rating because I have been using this tool since 2017, and I was in college at that time. Initially, I hesitated to use it as I was not very aware of the workings of Python and how difficult it is to manage its dependency from project to project. Anaconda really helped me with that. The first machine-learning model that I deployed on the Live server was with Anaconda only. It was so managed that I only installed libraries from the requirement.txt file, and it started working. There was no need to manually install cuda or tensor flow as it was a very difficult job at that time. Graphical data modeling also provides tools for it, and they can be easily saved to the system and used anywhere.

Incentivized

The thing I like the most is Visual Studio doesn't suffer from Microsoft's over eager marketing department who feel they need to redesign the UI (think Office and windows) which forces users to loose large amounts of productivity having to learn software that they had previously known.

Incentivized

Anaconda provides fast support, and a large number of users moderate its online community. This enables any questions you may have to be answered in a timely fashion, regardless of the topic. The fact that it is based in a Python environment only adds to the size of the online community.

Incentivized

Between online forums like StackOverflow, online documentation, MSDN forums, and the customer support options, I find it very easy to get support for Visual Studio IDE when I need it. If desired, one can also download the MSDN documentation about the IDE and have it readily available for any support needs.

Incentivized

I have experience using RStudio oustide of Anaconda. RStudio can be installed via anaconda, but I like to use RStudio separate from Anaconda when I am worin in R. I tend to use Anaconda for python and RStudio for working in R. Although installing libraries and packages can sometimes be tricky with both RStudio and Anaconda, I like installing R packages via RStudio. However, for anything python-related, Anaconda is my go to!

Incentivized

I personally feel Visual Studio IDE has [a] better interface and [is more] user friendly than other IDEs. It has better code maintainability and intellisense. Its inbuilt team foundation server help coders to check on their code then and go. Better nugget package management, quality testing and gives features to extract TRX file as result of testing which includes all the summary of each test case.

• It has helped our organization to work collectively faster by using Anaconda's collaborative capabilities and adding other collaboration tools over.
• By having an easy access and immediate use of libraries, developing times has decreased more than 20 %
• There's an enormous data scientist shortage. Since Anaconda is very easy to use, we have to be able to convert several professionals into the data scientist. This is especially true for an economist, and this my case. I convert myself to Data Scientist thanks to my econometrics knowledge applied with Anaconda.

Incentivized

• We've had hundreds of hours saved by the rapid development that Visual Studio provides.
• We've lost some time in the Xamarin updates. However, being cross platform, we ultimately saved tons of time not having to create separate apps for iOS and Android.

Incentivized