Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…
It is well suited for projects that are more discovery related. If this is a one-time project that we create a visual for, this would definitely make sense to use. If this is an ongoing analysis (monthly for example), we might look to another software that we would be able to automate a little further in how the visualization comes together
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
In comparison to other tools such as GraphWiz or Circos, Gephi comes with an intuitive, easy-to-use interface that makes it easy to load your data, and quickly start building all sorts of different graphs. There's absolutely no code that needs to be written for either loading or modeling. And without downloading additional plug-ins, Gephi ships with quite a few standard graph models, as well as some "fun" extras such as the Sierpinski triangle, and a variety of force atlas types.
Most of the layout types (maybe all) are highly configurable, which can make for extremely customized and unique displays of your data. Again, none of this requires the user to write any code. That said, it is possible to script custom functionality for your models, or even update the Java source code yourself, if you feel like getting technical. Gephi builds are available on GitHub, and the developers encourage people to contribute ideas, improvements, and plug-ins.
There's a plug-in for Gephi that allows for streaming data to update your model. This essentially allows you to create near realtime graphs of your data in motion. This plug-in was by far the biggest reaston we invested time in the product; to create animated data visualizations without exhaustive hours in development.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I (and many others) have had to expand Gephi's memory manually by experimenting with the configuration file. I'm glad it's possible, but it should be easier.
Gephi sometimes crashes inexplicably and loses your work, so I have developed a habit of explicitly exporting versions of my graphs as csv's, but I think this should be handled automatically in Gephi.
Because it is prone to crash, ideally, Gephi would help the user manage his/her use, by estimating processing and memory for very large tasks and prompting the user to confirm their requests before executing. Instead, I just tend to avoid certain functions.
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
While Gephi isn't perfect, it's a powerful tool for mathematical graph modelling that's hard to find in other products, particularly by way of its interface. It grants non-software developers access to a point-and-click way of creating accurate, beautiful visualizations that would normally take hours in other applications. The fact that it allows for live streaming data is also something that's hard to come by, at least for visualization software
Gephi is very intuitive and the fact that it shows its process helps the user understand what's going on. However, the animation features can really slow it down and there isn't a way to shut them off. Furthermore, the failures on saving mean you frequently have to start over. These problems disrupt the workflow and can be frustrating.
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
The interactivity in Gephi and the quality of the output figures are impressive. However, the selling point was the fact that we were able to link Gephi into our pipeline using Java's interface. Other products were less customizable and lacking of the sophistication Gephi provided without too much pain during the liking process.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
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.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I have only used the product for education purposes. I will not be the best person to provide details about ROI and business efficiency and customer service. I was personally very excited about the tool and am continuing my work on the tool.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
