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Based on our record, Plotly should be more popular than Evidence.dev. 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.
Https://opensource.com/article/20/4/plot-data-python gives some common options. What kind of plots are you trying to achieve? Interactive? Jupyter notebooks? Reporting? SVG or HTML output? You might also like to look at things like https://evidence.dev. - Source: Hacker News / 10 days ago
I'll ask another of the "how is this different" questions - how is this different from https://evidence.dev/ ? Quary seems a little like dbt + Evidence from what I can see. - Source: Hacker News / 11 days ago
We use echarts at https://evidence.dev and have been quite happy with it. We do a lot of embedded analytics and it's worked well for us. - Source: Hacker News / 27 days ago
It’s interesting to me how far you have pushed the SQL language in this framework, such that it truly is “SQL only”. The challenge as I see it with enabling analysts to build websites is that you need to build abstractions to get from familiar (SQL, yaml) - the language of analytics, to new (HTML, CSS, JS) - the language of the web browser As one of the maintainers of Evidence ( - Source: Hacker News / 3 months ago
Dataclips was my first experiences writing SQL. Writing code was a markedly better DX that building dashboards in Tableau, which is why I'm now working on https://evidence.dev - a SSG for creating data from SQL and markdown Previous HN discussions:. - Source: Hacker News / 3 months ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 6 months ago
If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: about 1 year 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: about 1 year 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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