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.
Based on our record, Plotly should be more popular than Count.co. It has been mentiond 29 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
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
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 5 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: 11 months ago
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: 12 months ago
I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: about 1 year ago
Plotly Dash is a great framework for developing interactive data dashboards using Python, R, and Javascript. It works alongside Plotly to bring your beautiful visualizations to the masses. - Source: dev.to / over 1 year ago
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