Co-founder of Kyso here. We will be opening up the platform before the end of the year. So going forward, it will be free to teams of all sizes. If anyone is interested, feel free to reach out to me at [email protected]
Have you ever considered Kyso (https://kyso.io) (disclaimer - I'm a co-founder)? I could be way off, and it would be a corner case for us right now, but it seems we'd fit all your requirements:
* We sit on top of git, which remains the single source of truth for your code - versioning, reproducibility, etc.
* Python & R notebooks or simple markdown (also on the web app itself).
* Show or hide code.
* Simple links for sharing reports.
* Tagging.
* Comprehensive search - by tag, keyword and content (soon).
Would be really interesting to hear your thoughts on the fit.
Kyso is a central knowledge hub for sharing and collaborating on technical reports posted by the company's data scientists, engineers & analysts, so everyone can read and learn from the generated insights.
We are in the process of building out our library of templates - these are ready-made boilerplates for various data science tasks that are designed to allow new teams to get their reports deployed as quickly as possible. An example of such templates can be found below:
Awesome article - I'm wondering, for "Publishing the Notebook" part of the workflow, have you ever seen Kyso (https://kyso.io) - disclaimer, I'm a founder. We started Kyso to make it easier to communicate insights gained from analysis to non-technical people by converting data science tools (e.g. Jupyter Notebooks) into conversational tools in the form of blog posts. You can make public posts or have an internal "data blog" for your team, where you push your work to Github and it is reflected on Kyso. Would love to hear your thoughts on how it could fit into existing workflows.
It's scary seeing the evolution of the effects of climate change over time. How anybody can continue to deny it is unbelievable. This [1] plots out global average temperatures since the Industrial Revolution, month by month.
Hey - not OP but I wrote the article. There was a lot of discussion about recency bias in that thread, including the graph you shared and I decided to expand on the analysis. Note there are a few other graphs in my post. I did just draw this up quickly yesterday. But you're right, sorry - I should have cited your comment in my post. Adding it now.
I don't know if that is down to recency bias, but rather the sheer number of fans for that particular genre. There are not many movies in the top 50 you could reasonably make that same argument for.
Also, I'm not sure you could make that argument for IMDB's top 250 TV series [1], but maybe that's just my own preferences speaking.
Well, it's one of the ways to post to Kyso, but yeah, you can synchronize your Github repositories to Kyso and choose the notebooks you want to have rendered. When you push changes to the repo, the sister post on Kyso will be automatically updated.
Hey, I posted the notebook by the OP. Thank you for your feedback! You're correct in saying that FB Prophet is for forecasting time series with strong seasonal effects. FB Prophet was the model used in the original script I found & the main point here was simply to make the notebook more readable on kyso, which has quite a few non-technical readers. I've worked a lot with ARIMAs before for financial/economic data and I like the idea of comparing the results between the two, and maybe even extend the time frame. So 1. I think that'll be my next project and 2. if your project is public I'd love to give it a read when published.