Anaconda vs. ETAP PS

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

ETAP is highly recommended for evaluating static conditions in electrical power systems, whether in high or medium complexity networks. For example, study of load flow, analysis of frequency harmonics.

On the other hand, I would not recommend ETAP for the simulation of highly complex control systems that require a dynamic analysis of the variables.

• 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

• Excellent facility for the design of electrical systems, since it has multiple options and configuration.
• Truly intuitive, it is easy to adapt to the user interface, so the learning curve is very fast.
• It offers a wide variety of electrical studies that can be carried out, therefore it is very versatile for multiple applications.

• 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

• Perhaps the interface is somewhat confusing the first time you use the program.
• It offers a wide configuration, which can be overwhelming.
• Sometimes the program can freeze depending on the size of the electrical grid that is being simulated. This also depends on the software requirements.

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

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

ETAP PS is really easy to use. When recreating the power system to be simulated, it is easy to obtain a result close to reality due to the multiple components offered in the interface. As for the electrical studies available, they are simple to execute and require really little configuration to make them work, always offering a wide variety of options to adjust the program to the simulation of the desired condition.

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

Sometimes when the program crashes for a random reason, it is difficult to find a direct solution to the problem. I think better documentation is needed for this type of case. Still, more and more people are sharing their work on the web, making it easier to orient yourself when these issues occur.

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

Simulink allows to analyze and simulate different variables with respect to time in an electric power system, but it is more focused on visual programming On the other hand, ETAP is better designed for static simulation of power systems, offering options and studies in a very more direct and easier to execute.

• 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

• Improves the reliability of the electrical system.
• Study of the system operations, allowing a better adjustment of the facilities that are in production.
• Provides results that allow you to select solutions for energy saving.