Likelihood to Recommend I've created a number of daisy chain notebooks for different workflows, and every time, I create my workflows with other users in mind. Jupiter Notebook makes it very easy for me to outline my thought process in as granular a way as I want without using innumerable small. inline comments.
Read full review I would recommend Vim in any scenario where text files have to be viewed, created, or edited on GNU/Linux computers. Regardless if you need to quickly change a few things in a configuration file, or you need to write up a full document, Vim is great. I wouldn't use Vim to view, edit, or create anything that requires "rich-text". In other words, if you need to format the text (bolding, font colours, word-art, etc), then Vim isn't the tool to use.
Read full review Pros Simple and elegant code writing ability. Easier to understand the code that way. The ability to see the output after each step. The ability to use ton of library functions in Python. Easy-user friendly interface. Read full review The efficient modal editing makes it very fast to write/edit code as I think of it. The customization and wide range of plugins let me do very specific things and automate parts of my workflow. The fact that it runs inside a terminal simplifies my window management and just becomes another Tmux window in my workflow. Read full review Cons Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings. Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name. Read full review Without a doubt the hardest program to learn. It is a completely different paradigm of thinking compared to other editors By default it doesn't have lots of fancy features you would find in larger IDE programs like code completion and linking It lives in the command line so a user has to be comfortable with this interface Read full review Usability Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
Read full review I don't consider the steep learning curve to be a hinderance on the overall usability. I would rate this a ten, but to be honest a lot of people do get hung up at the beginning and just abandon it. However, for people who have made the moderate effort to get over the hump, nothing can be more usable.
Read full review Support Rating I haven't had a need to contact support. However, all required help is out there in public forums.
Read full review There is no commercial support for Vim. Thus, it will not get a mark beyond 5. However, community support is very good. You can easily find solutions for most of the problems in the community.
Read full review Alternatives Considered With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better business decisions and save cost to the company. It stacks up better as we know Python is more widely used than R in the industry and can be learnt easily. Unlike
PyCharm jupyter notebooks can be used to make documentations and exported in a variety of formats.
Read full review Vim's keybindings are a lot more complex than Notepad++. With that, comes a whole bunch of capability that Notepad++ just can't match. Emacs is comparable, in terms of capabilities--because Vim is built into so many unix systems, I chose to learn it instead of Emacs. Knowing both probably isn't a bad idea, but there's enough to learn in either camp to keep you busy
Read full review Return on Investment Positive impact: flexible implementation on any OS, for many common software languages Positive impact: straightforward duplication for adaptation of workflows for other projects Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration Read full review It always increases productivity. Sometimes feature discovery is not easy. It could be documented well like how to install a plugin and if it supported well or not. Read full review ScreenShots