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Based on our record, Plotly should be more popular than Chartist.js. 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.
Here's a JS framework that seems to do almost everything you want (outside of not requiring a JS framework, of course). It's a Sass project and uses Node modules, so I wasn't able to get it running using vanila js. (I'm not much of a JS dev.) I'm also interested in other players in this space. SVG seems like the ideal way to make static plots. https://gionkunz.github.io/chartist-js/. - Source: Hacker News / 2 months ago
If you are sending the data to a website, or serving the website yourself, using JSON as the data format will be the easiest. Personally I never use cloud services and I just use a Javascript charting library like https://gionkunz.github.io/chartist-js/ (it supports real-time graphs) on a web page that is self-hosted (run a server on the ESP32). Source: 11 months ago
The author went through the effort of creating a marketing site with documentation and examples. https://gionkunz.github.io/chartist-js/. - Source: Hacker News / over 1 year ago
With django-controlcenter you can have all of your models on one single page and build beautiful charts with Chartist.js. Actually they don't even have to be a django models, get your data from wherever you want: RDBMS, NOSQL, text file or even from an external web-page, it doesn't matter. - Source: dev.to / over 1 year ago
Anyone here have some good suggestions for mature, easy to use graph libraries for Vue 3? Maybe I should write a wrapper around Chartist myself... Source: about 2 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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