dash
d3
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dash | d3 | |
---|---|---|
56 | 277 | |
20,472 | 107,600 | |
1.5% | 0.3% | |
9.6 | 8.4 | |
4 days ago | 15 days ago | |
Python | Shell | |
MIT License | ISC License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dash
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dash VS solara - a user suggested alternative
2 projects | 13 Oct 2023
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[Python] NiceGUI: Lassen Sie jeden Browser das Frontend für Ihren Python-Code sein
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
- Visualizing parquet in s3 bucket for data analysis?
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Little guidance of a python newbie
You could use something like Streamlit or Dash. In any case you will be accessing your app through the browser.
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Launch HN: Pynecone (YC W23) – Web Apps in Pure Python
Useful list. Dash & bokeh as two more in the space
https://github.com/plotly/dash
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Python projects with best practices on Github?
I also heard of Dash which serves the same purpose I guess, but I think it has more to offer.
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4 Streamlit Alternatives for Building Python Data Apps
Plotly is a plotting library, and Dash is their open-source framework for building data apps with Python, R or Julia. (Dash also has an Enterprise version, but we'll focus on the open-source library here.)
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NiceGUI: Let any browser be the frontend for your Python code
Of course there are valid use cases for splitting frontend and backend technologies. NiceGUI is for those who don’t want to leave the Python ecosystem and like to reap the benefits of having all code in one place. There are other options like Streamlit, Dash, Anvil, JustPy, and Pynecone. But we initially created NiceGUI to easily handle the state of external hardware like LEDs, motors, and cameras. Additionally, we wanted to offer a gentle learning curve while still providing the ability to go all the way down to HTML, CSS, and JavaScript if needed.
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Sharing interactive Plotly graphs
looks like you can get it manually (albeit with a loss of interactivity) https://github.com/plotly/dash/issues/145
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Containerizing Shiny for Python and Shinylive Applications
Shiny is a framework that makes it easy to build interactive web applications. Shiny was introduced 10 years ago as an R package. In his 10th anniversary keynote speech, Joe Cheng announced Shiny for Python at the 2022 RStudio Conference. Python programmers can now try out Shiny to create interactive data-driven web applications. Shiny comes as an alternative to other frameworks, like Dash, or Streamlit.
d3
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A visual guide to Vision Transformer – A scroll story
Yes this was done with a combination of GSAP Scrolltrigger https://gsap.com/docs/v3/Plugins/ScrollTrigger/ and https://d3js.org/
- Ask HN: Tips to get started on my own server
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Full Stack Web Development Concept map
d3 - very power visualization library enabling dynamic visualizations. docs
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Observable 2.0, a static site generator for data apps
Yep, Evidence is doing good work. We were most directly inspired by VitePress; we spent months rewriting both D3’s docs (https://d3js.org) and Observable Plot’s docs (https://observablehq.com/plot) in VitePress, and absolutely loved the experience. But we wanted a tool focused on data apps, dashboards, reports — observability and business intelligence use cases rather than documentation. Compared to Evidence, I’d say we’re trying to target data app developers more than data analysts; we offer a lot of power and expressiveness, and emphasize custom visualizations and interaction (leaning on Observable Plot or D3), as well as polyglot programming with data loaders written in any language (Python, R, not just SQL).
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Using Deno with Jupyter Notebook to build a data dashboard
D3.js: A robust library to visualize your data and create interactive data-driven visualizations.
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What is the technology stack used to create these live charts?
They are images so it could be any number of things, datawrapper, charts.js, d3.js to name a few options.
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Animated map showing frequency and location of births around the world [OC]
I made this interactive visualization that attempts to show the real-time frequency and location of births around the world. A country’s annual births (i.e. the country’s population times its birthrate) were distributed across all of the populated locations in each country, weighted by the population distribution (i.e. more populated areas got a greater fraction of the births). Data Sources and Tools Population and birthrate data for 2023 was obtained from Wikipedia (Population and birth rates). Population distribution across the globe was obtained from Socioeconomic Data and Applications Center (sedac) at Columbia University. Data is processed and visualized at a 1 degree x 1 degree resolution, each of which has a different probability of a birth occurring in a specific time period. D3.js was used to create the map elements and html, css and javascript were used to create the user interface.
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How do you implement library types?
When I go to the homepage of types/d3 the only hint for any kind of documentation is what seems to be the main github page of d3. It's highly possible I'm missing something here, so sorry if I am but I can't find any documentation of how you are supposed to type these library objects.
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The top 11 React chart libraries for data visualization
Website: D3.js official site
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Frontend development roadmap
D3js
What are some alternatives?
streamlit - Streamlit — A faster way to build and share data apps.
echarts - Apache ECharts is a powerful, interactive charting and data visualization library for browser
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
GoJS, a JavaScript Library for HTML Diagrams - JavaScript diagramming library for interactive flowcharts, org charts, design tools, planning tools, visual languages.
panel - Panel: The powerful data exploration & web app framework for Python
vis
uvicorn - An ASGI web server, for Python. 🦄
d4 - A friendly reusable charts DSL for D3
Flask - The Python micro framework for building web applications.
svg.js - The lightweight library for manipulating and animating SVG
nicegui - Create web-based user interfaces with Python. The nice way.
sigma.js - A JavaScript library aimed at visualizing graphs of thousands of nodes and edges