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Why Jupyter is data scientists’ computational notebook of choice

nature.com

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Re: Why Jupyter is data scientists’ computational notebook of choice

#221

Post by ontouchstart »

Many comments are about implementation details such as JSON format of Jupyter and comparing user experience with IDE and shell and fail to see the fundamental difference between Emacs and Jupyter, which is in this quote in the article:

“In many cases, it’s much easier to move the computer to the data than the data to the computer,” says Pérez of Jupyter’s cloud-based capabilities. “What this architecture helps to do is to say, you tell me where your data is, and I’ll give you a computer right there.”

Re: Why Jupyter is data scientists’ computational notebook of choice

#222

Post by jononor »

huac wrote: post #181
ChuckMcM wrote: post #172

I see Jupyter notebooks as the next step in spreadsheets with more code foundation and different media support. For me the interface doesn't work as well as I would like but I can see the potential. My brother in law wants something like this for structural analysis reports where the code, data and report are all one thing that can be pulled out and examined. Watching the new iPad announcement today I think this is s…

yeah, i have a use case now where we pull data from a database, manipulate it, and then have a final table/csv/dataframe/whatever. the problem is then how to share this with non-technical users. in an ideal world, this would get inserted into a google sheet, and that sheet would just update daily after new data is loaded into the database. i'm pretty sure this is a usecase which others have and curious what people us…

Google Sheets has an API. So if putting the output there is the ideal, just use that API from Python?

Re: Why Jupyter is data scientists’ computational notebook of choice

#223

Post by projectramo »

makmanalp wrote: post #61
projectramo wrote: post #35

Here are the issues with Jupyter, and most other flavor, of notebook: 1. variables have to be explicitly output The most important tool for programming, for me, is that window that shows you the current state of all the variables. When I step through a program, I look at the state. 90% of my debugging solutions come from seeing that variable doesn't have the right state. 2. Intellisense For the love of god, I do not…

Re #2, if you haven't tried the newest versions recently (and especially with the jupyterlab beta which has a nicer completion GUI), I'd encourage you to take a look! It's come a long way, along with the library that's doing the completions under the hood.

Thanks for the tip. Will take a look. I thought I was using the latest version.

Re: Why Jupyter is data scientists’ computational notebook of choice

#224

Post by projectramo »

cirgue wrote: post #100
projectramo wrote: post #35

Here are the issues with Jupyter, and most other flavor, of notebook: 1. variables have to be explicitly output The most important tool for programming, for me, is that window that shows you the current state of all the variables. When I step through a program, I look at the state. 90% of my debugging solutions come from seeing that variable doesn't have the right state. 2. Intellisense For the love of god, I do not…

Re #1: There's a plugin in nbextensions that shows variable values a la spyder.

Good to know. Will check it out.

Re: Why Jupyter is data scientists’ computational notebook of choice

#225

Post by projectramo »

pavanagrawal123 wrote: post #57
projectramo wrote: post #35

Here are the issues with Jupyter, and most other flavor, of notebook: 1. variables have to be explicitly output The most important tool for programming, for me, is that window that shows you the current state of all the variables. When I step through a program, I look at the state. 90% of my debugging solutions come from seeing that variable doesn't have the right state. 2. Intellisense For the love of god, I do not…

Hey There! I'm trying to solve the issue of IntelliSense.. I'm building/improving Jupyter Notebooks inside VSCode: https://github.com/pavanagrawal123/VSNotebooks . It's a fork from another extension somebody already built, but all activity is dead, so I'm starting up dev on an active fork. I'd love to hear any feedback y'all have! :) Also planning to add some nice debug features, plus hopefully integration into the i…

Thanks for working on this. We’re converging on the Bret Victor IDE

Re: Why Jupyter is data scientists’ computational notebook of choice

#226

Post by brians »

narwally wrote: post #213
zmmmmm wrote: post #204

As with so many things python related (including python itself), I am perplexed by how willing people seem to be to fall in love with solutions that have so many limitations and problems. I find Jupyter just barely usable. I constantly have issues with editing in the cells, diagrams not sizing correctly, cells accidentally displaying huge amounts of data and freezing my browser, complete failure of autocompletion in…

I feel the same way, especially as an emacs user. Org-babel seems to be a superior implementation of the same idea. Org is just a text document, so git and git diffs work. I can use any combination of languages I want in a document and have them running in different sessions. And best of all I can edit code blocks using my customized major mode for that language. On top of that you get all the goodness that comes wit…

I expect jupyter notebooks to keep an environment consistent between cells. Org-Babel doesn’t generally do this. A Good notebook environment is more like a lisp buffer with block comments.

Re: Why Jupyter is data scientists’ computational notebook of choice

#227

Post by bodkan »

azag0 wrote: post #164

I love Jupyter Notebook for experimenting and rapid creation of reports, but dislike it for not being able to use my editor and for intermingling inputs and outputs in a single file. So I'm working on an alternative frontend to Jupyter kernels, which is heavily inspired by KnitR: https://github.com/azag0/knitj It is still being developed, but it's functional and I use it every day.

This looks incredible! Does your project already support other language kernels than the Python kernel?

I use R for 90% of my work, but most of it has been happening in Jupyter notebooks (which I'm not a huge fan of, despite practically living in them for the past 4 years of my life).

Thanks for sharing!

Re: Why Jupyter is data scientists’ computational notebook of choice

#228

Post by mmq »

reilly3000 wrote: post #127

Does anybody know of a good hosted solution of JupyterHub? I made a neat notebook that I needed to share with my non-technical team, it was using iPyWidgets to do some interactive modeling, but they each needed to be able to use it independently. It has private data so I couldn't use Binder. I've been following Zepl.com for a long time, but couldn't use them here because Zepplin doesn't support iPyWidgets. Pretty soo…

Polyaxon, https://github.com/polyaxon/polyaxon, is an open source platform that tries to simplify not only running notebooks on kubernetes, but also tries to solve issues related to scaling, tracking, and reproducibility.

Disclaimer, I work on Polyaxon.

Re: Why Jupyter is data scientists’ computational notebook of choice

#229

Post by hatmatrix »

gaius wrote: post #209
zmmmmm wrote: post #204

As with so many things python related (including python itself), I am perplexed by how willing people seem to be to fall in love with solutions that have so many limitations and problems. I find Jupyter just barely usable. I constantly have issues with editing in the cells, diagrams not sizing correctly, cells accidentally displaying huge amounts of data and freezing my browser, complete failure of autocompletion in…

it's a dumpster fire - in 2018 there should be something so much better than this In 1998 I was using a tool called MathCAD that provided a notebook interface running as a plugin to MS Word. In 2018, Jupyter is still not as good as that. Some things are just not meant to be webpages.

If I recall correctly, MathCAD was so much point and click to enter mathematical formulas that I found it very cumbersome to use.

Re: Why Jupyter is data scientists’ computational notebook of choice

#230

Post by jrumbut »

Immortalin wrote: post #136
jrumbut wrote: post #90

Earlier quoted context omitted.

I think it speaks to people's desire for a quick and easy to set up basic GUI creator with an editor that allows inline code editing, and no need to deal explicitly with the client server interaction. I myself, as someone who likes to create really solid and maintainable tools, have fallen into the notebook trap and written things like "change the month in cell 22 then execute cells 1 through 3 and 20 through 27 to u…

Yes. It's called Microsoft Excel. Software engineers don't like VB for the same reason they don't like Python-in-a-notebook but you cannot deny its effectiveness.

You're right about what excel is (and the whole VB ecosystem for that matter), but I think the critical difference is that the language and environment are very different. If I know the smallest amount of python (or R) I can leverage Jupyter notebooks and it is intuitive.

To really get something great out of excel you have to learn excel. I think that difference is almost as important as the excel stigma.

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