Count is a new type of data analytics application, where everything is based around notebooks.
Notebooks contain all of your analytics queries, alongside rich text, images, videos, and interactive controls. A notebook can be a simple static document, a fully interactive application, or anything in-between. They are backed up as you write, use state-of-the-art rendering technology to take full advantage of your machine, and scale down to stay readable on mobile.
Count connects to your data warehouse to run queries, so the data you see is always up-to-date. It also (optionally) intelligently caches results to minimise the load on your databases.
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Example notebooks are included in the repo and can be previewed using nbviewer:. Source: over 1 year ago
Nbviewer (https://nbviewer.org/): very easy to use for smaller jupyter notebook that does not require heavy rendering. Source: over 1 year ago
Nbconvert renders everything exactly as it looks in your notebook app into a read-only HTML version and is what GitHub uses for notebooks. Interactive plots from Bokeh, Holoviews, etc can still work if you trust the JS, and since editing notebooks while showing them during a meeting usually doesn't go well, read-only is probably good enough (eager to hear feedback on this point though). The nice thing is that... Source: over 1 year ago
Just as a heads up, I used plotly to generate a lot of the charts, so you'll need to view it from an nbviewer like nbviewer.org. Source: about 2 years ago
I used a lot of plotly not knowing that Github wouldn't show it, so you'll need notebook viewer like nbviewer.org to see some of the charts. Source: about 2 years ago
Hi Reddit, after lurking here a while I've finally got something interesting to share - a new feature I've been working on at Count (https://count.co), which I wrote a blog post on here:. Source: 5 months ago
Hi HN, after seeing a lot of data engineering discussion here I thought it would be interesting to share a new feature I've been working on at Count (https://count.co). We've made possible to import and execute dbt models, compiling them on the fly with a custom compiler, and view results alongside other collaborators in real time. We built this because we heard feedback from our customers that debugging and... - Source: Hacker News / 5 months ago
Count | Senior Software Engineer | REMOTE within UK/Europe | Full-time | https://count.co Count is like Jupyter, Tableau and Miro combined in one tool. Data teams at some of the world's leading scale-ups use it for everything from iterating data models to performing deep dive analyses and telling impactful stories backed by data. We're a small team of 8, and we're looking for experienced software engineers who are... - Source: Hacker News / 6 months ago
Full disclosure: I do work for count.co, the canvas in which the guide was built. Source: 10 months ago
Nice article! When we wrote the instanced WebGL line renderer for https://count.co one of the tricky parts was switching between mitre and bevel joins based on the join angle - for very acute angles the mitre join shoots off to infinity. Another nice extension (that we are yet to implement) is anti-aliasing, but I think that requires extra geometry to vary the opacity over. - Source: Hacker News / almost 3 years ago
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