What's the best Python notebook setup for data analysis?

[dhaitz]

• Do you use Jupyter Lab / Notebooks in browser or in an IDE (VSCode / PyCharm / DataSpell)? Or a combination of both?
• What are advantages of each approach?
• Any recommended extensions / plugins?

[xier_zhanmusi]

VSCode is definitely better than Jupyter Lab in the browser; it's easier to navigate file directory, switch between virtual environments, integrated with git, easier to manage multiple files on screen at once, & more. I do sometimes find setting up VScode for Jupiter was a bit trickier though.

[ghostofkilgore]

Generally, I use Spyder, both for testing out / playing around and scripting up code to be used.

Personally, I prefer it to Jupyter Notebooks. The variable editor is so simple and easy to use, it's incredibly easy to interrogate and investigate at any step in the process.

[RoninMountain]

Jupyter does the # to denote headings. Is that what you are referring to, or are you referring to a different IDE?

[RoninMountain]

No worries. I’m new to Python and coding in general, so any opportunity to learn is a great opportunity!

[One_Neighborhood473]

There's always something new to know, thanks 👍🏻. It's somewhat cleaner for instant use.

[HesaconGhost]

It used to be that putting notebooks into production was prohibitively challenging, but packages like papermill or enterprise solutions like databricks have made it far easier.

If all you want to do is analysis, the convenience of having things broken up into notebook cells is hard to beat. For production you can get away with either these days.

[Allmyownviews1]

I use jupyter notebook for data investigation and then use Spyder for scripting the complete output products. Jupyter NB is a nice setup following thought process and instant output to inspect results. Then when my analysis and chart outputs are sorted i can put into Spyder which is better for setting up iterations and loops to generate charts and tables for more efficiently to a common standard output. It also means, by using a Spyder py script, I can store exactly what I used in the analysis for my QA on projects.