eoinmurray92

you might want to give Kyso a try (Im a cofounder):

https://about.kyso.io/

We render jupyter notebooks, markown and html - we dont host running jupyter environments -> but we focus on making the experience of sharing with non-techies on your team easy. So can show/hide the code, get comments etc.

Monopsony can happen too

Kyso | Full-time JavaScript/Backend Engineer | Valencia, Spain but job is remote within the EU | with equity | kyso.io

https://angel.co/company/kyso-2/jobs/807083-software-enginee...

Hello all ! I'm Eoin one of the co-founders of Kyso. We are a small, fast growing, venture funded (Lunar Ventures & Techstars NYC) startup based in Valencia, Spain. Our stack is a typical MongoDB/Node.js backend with a Next.js/React.js frontend.

Kyso is a company’s central data insights hub where data scientists can post reports in a way that everyone on the team can read and learn from them. We are compatible with all the common data science tools, yet make the reports readable for non-technical people - bridging the gap between the data team and the rest of the company. Kind of like Notion (or Confluence), but for data analysis. 2/3 founders already have an exit - so this isn't our first rodeo.

It’s our first hire (equity included) so if you want to get into a fast growing startup early - please apply!

Kyso | Full-time JavaScript/Backend Engineer | Valencia, Spain but job is remote within the EU | with equity | kyso.io

https://angel.co/company/kyso-2/jobs/807083-software-enginee...

Hello all ! I'm Eoin one of the co-founders of Kyso. We are a small, fast growing, venture funded (Lunar Ventures & Techstars NYC) startup based in Valencia, Spain. Our stack is a typical MongoDB/Node.js backend with a Next.js/React.js frontend.

Kyso is a company’s central data insights hub where data scientists can post reports in a way that everyone on the team can read and learn from them. We are compatible with all the common data science tools, yet make the reports readable for non-technical people - bridging the gap between the data team and the rest of the company. Kind of like Notion (or Confluence), but for data analysis. 2/3 founders already have an exit - so this isn't our first rodeo.

It’s our first hire (equity included) so if you want to get into a fast growing startup early - please apply!

At Kyso [1] we let you do this (I'm one of the founders) - you can run Jupyterlab online and start servers inside Jupyterlab that you can share with the world (Jupyterlab will run on instance-id.cloud.kyso.io).

You can install viola and then just run it on port 8000 from within the jupyterlab terminal and you can share the url with anyone (it will be instance-id-8000.cloud.kyso.io)

We're actually thinking of supporting Viola natively in the next few weeks, what kind of app do you want to run?

[1] https://kyso.io

Or at least each page load will be slow and memory intensive for the server

If it spawns a new kernel for each request it will be very slow no?

Hi - founder of Kyso here, thanks for your feedback we will get to work fixing those issues now

I think it's been interpreted as recent movies not recent votes.

These iPhone price graphs would be better if they accounted for inflation - which still shows a large increase in price, especially if you look at the flagship phones.

https://kyso.io/eoin/iphone-prices

And you need to pay an absolute premium for this pricacy - I've plotted the price of iPhone prices increase here and even after adjusting for inflation the price growth is really high. Especially if you look at the flagship phones

https://kyso.io/eoin/iphone-prices

At Kyso [1] we are really concerned about climate change and environmental damage in general - one of my co-founders actually started as an environmental scientist. We make tools to make data-visualisations easier using Jupyter but we've been wanting for the last few weeks to really focus the content that we write on climate change, from a data point of view.

I'm wondering does anyone here have experience with this - where do you source data-sets, what kind of charts have the most impact on people - is this even worth doing?

We've made a few studies before going through Co2 rates (https://kyso.io/KyleOS/atmospheric-co2-concentrations-2), which countries are on the most sustainable path (https://kyso.io/KyleOS/environment-ranking) and per capita meat consumption (https://kyso.io/eoin/per-cap-meat-consumption) but we'd love to get some advice on how to really target high impact work in this area

[1] https://kyso.io I'm a founder

At Kyso (https://kyso.io) we see a lot of people get hired into data-science jobs and the biggest success factor that I've personally seen is having some example's of projects that the candidate has worked on. This can be either public projects online (thats what we started Kyso to help with!) or a description of a project they worked on while studying/working.

Something I've noticed about data-science candidates is that they are very happy to jump into the technical details of an implemented model - but sometimes struggle on is communicating the reasons for the model in the first place and how it can help the company/research project. A lot of data-science projects are smaller ad-hoc jobs where the data scientist is trying to answer some business question and here communication is a vital skill.

The UK currently has larger complaint numbers than France or Germany [1] at around 6,000-16,000 each which is weird, but it does show that many people are taking individual privacy rights seriously

[1] https://kyso.io/eoin/gdpr-complaints-for-various-eu-countrie...

I should not that anyone can contact me at eoin [at] kyso.io

Yeah so its mostly a split between Jupyter and R Studio - but Jupyter can mean different languages

Im not sure - we have large teams using Kyso as a knowledge base for data-science work and there's also Airbnb's knowledge-repo which originally inspired us so from my point of view there is decent evidence for the need for this

This is a really good idea, and I've been planning to write said guide for a while.

I think there is a lot to do with organising and formatting the notebooks, and the %run command works a treat for me when breaking a project into multiple notebooks

Ah yeah ok - we are not planning GPU support soon - what if we created one of those one-click deploy a VM to aws/digital-ocean buttons and from there if you wanted to post to Kyso you could do it with git or our jupyter lab plugin.

You get most of the same experience and you can even customise various of the steps?

Mostly so you don't need to convert to PDF and so that you can host the reports in a central place where everyone can read them technical or not.

Like an internal wiki for a companies data-science where the technical people can communicate their work to the non-technical people with a pretty seamless experience

The OP post is a Jupyter notebook itself and if you sign up to Kyso you can actually Jupyterlab on our cloud and the post the notebooks to the web, or make them private on the paid plan - is that what your looking for?

Thats true if you sharing with someone who also understands the code - we think that the feature allows you to share the notebooks with a completely non-technical audience.

Image you had a notebook to analyse sales data and you needed to present the results to your CEO (who perhaps cannot code) - this feature lets you present the notebook as is, without needing to prepare a report in some other format

How do you share and collaborate on the notebooks internally - I'd love to get your thoughts on our Kyso for teams system [1] if you would be willing to chat?

[1] https://kyso.io/for-teams

We actually have a few ways to publish your notebooks.

Upload directly, import from Github or use our plugin to publish from Jupyterlab itself - all those methods are outlined on our docs page: https://kyso.io/docs

OP and Founder of Kyso here - we built Kyso to make it easier to blog your notebooks to the public and also to make them easier to share in teams.

The linked post is actually a Jupyter notebook itself - analysing the number of notebooks on Github.

A key element with Kyso is that the code is hidden by default to make it readable to non-technical people but you can click on the "code hidden" button on the top right to see the code in full.

If you want to give Kyso a go - sign up and import from Github directly on this page: https://kyso.io/github, or upload using this page: https://kyso.io/create/study

Yeah this is true but sometimes R notebooks also refers to R studio notebooks - https://rmarkdown.rstudio.com/lesson-10.html

This is what we made Kyso for - the linked post is actually a Jupyter notebook itself, the code is hidden by default to make it readable to non-technical people but you can click on the "code hidden" button on the top right to see the code in full.

If github is not working for you well for your notebooks. You can try Kyso by signing up and importing your notebook from Github directly on this page: https://kyso.io/github, or upload it using this page: https://kyso.io/create/study

Disclaimer - I am OP and founder of Kyso

Here's a guide to using Github+Kyso [1] to publish your type of article to the web, it should be a very similar workflow to github pages, and you can use any of the popular python visualization libraries - we support plotly, bokeh, vega, altair, matplotlib etc.

https://towardsdatascience.com/publish-data-science-articles...

[1] Disclaimer: I'm the CEO of Kyso

Plotly with Cufflinks is pretty great to integrate with pandas (wide range of quick examples here: https://kyso.io/KyleOS/cufflinks-intro)

I should be pretty easy to set this up with Dash by plotly, and you can host in various places.

Here a guide we've written for an app where you can drag and drop a file and get a chart from it.

https://kyso.io/KyleOS/creating-an-interactive-application-u...

But you can extend to take an SQL query or maybe to set up an external api call.