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Based on our record, Plotly should be more popular than Vega Visualization Grammar. It has been mentiond 30 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.
This looks interesting but I’m pretty sure it’s not the first declarative charting tool. (Eg Vega https://vega.github.io/vega/). - Source: Hacker News / 15 days ago
Hi HN – Excited to share a beta for Minard, a new data visualization toolkit we've been working on that lets you generate publication-quality charts with simple natural language (throw away your matplotlib docs and rejoice!). Upload or import CSVs, Excel, and JSON, give it a spin, and please let us know what you think! (Long format data works best for now) For those curious, the stack is a simple Django app with... - Source: Hacker News / 2 months ago
I recently added support for plotting XGBoost models using Vega (https://vega.github.io/vega/) into the XGBoost Elixir API (https://github.com/acalejos/exgboost). Since EXGBoost supports loading trained models across different APIs, you can even train using the Python API and then plot using this Elixir API if you prefer. - Source: Hacker News / 5 months ago
The Data Source is from devjobsscanner (I am basically the owner, so I have the data) an the tool used to make the chart is Vega. Source: about 1 year ago
It’s based on Vega https://vega.github.io/vega/ which means it’s an already matured backend. Vega-lite is the Javascript package and Altair is the Python. Source: over 1 year ago
How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 16 days ago
For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 7 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: over 1 year ago
Vega-Lite - High-level grammar of interactive graphics
D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.
Chart.js - Easy, object oriented client side graphs for designers and developers.
picasso.js - Turn boring data into a visual masterpiece using picasso.js, an open-source library from Qlik.
Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application
Observable - Interactive code examples/posts