D3.js vs. Jupyter Notebook

It's well suited for dynamic data, especially when multiple users are using the application and generating data, it helps us to get analytics of the data for users.

Incentivized

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.

Incentivized

• It provides multiple ways of visualizing data easily.
• It is fast and light on system resources. It is built with JavaScript and visualizations can be easily hosted on the web across browsers.
• It has a huge community backing it so it is easy to find people to help with whatever you're doing.

Incentivized

• 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.

Incentivized

• Hard to code, not a kids play toy.
• No tutorial from official documentation.
• Requires web development experience.

Incentivized

• 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.

Incentivized

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.

Incentivized

Support can be improved by providing more educational videos.

Incentivized

I haven't had a need to contact support. However, all required help is out there in public forums.

Incentivized

Protoviz does not require as much knowledge of programming to build visualizations as with D3.js or Google Charts. Highcharts or AnyChart are other alternatives that are more specific to building charts only

Incentivized

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.

Incentivized

• Rapid Development using templates helps faster delivery of the project.
• Documentation requires a lot of time to study.
• D3 creates high-quality visual effects which can be used over large screens.

Incentivized

• 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

Incentivized