Plotly Reviews

Vega-Lite Reviews

Plotly mentions (30)

• Essential Deep Learning Checklist: Best Practices Unveiled

  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 / 18 days ago

• Python equivalent to power bi/power query?

  For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 7 months ago

• Junior Developer asked to make Saaas in first month.

  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

• PSA: You don't need fancy stuff to do good work.

  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

• Wait, but I thought they were the same thing?

  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 mentions (23)

• Show HN: I made first declaritive SVG,canvas framework

  We use the slightly simpler vega-lite from the same group. It typically gets us 98% of the way there quite quickly. Its from the same team, just a more simple wrapper around D3. https://vega.github.io/vega-lite/. - Source: Hacker News / 16 days ago

• Ask HN: What's the best charting library for customer-facing dashboards?

  I like Vega-Lite: https://vega.github.io/vega-lite/ It’s built by folks from the same lab as D3, but designed as “a higher-level visual specification language on top of D3” [https://vega.github.io/vega/about/vega-and-d3/] My favorite way to prototype a dashboard is to use Streamlit to lay things out and serve it and then use Altair [https://altair-viz.github.io/] to generate the Vega-Lite plots in Python. Then if... - Source: Hacker News / 2 months ago

• Gnuplotlib: Non-Painful Plotting for NumPy

  I also have difficulties with Gnuplot and Matplotlib. I like Vega that allows me to create visualisations in a declarative way. If I really need something special I go with d3.js, which had a really steep learning curve but with ChatGPT it should have become easier for beginners. [1] https://vega.github.io/vega-lite/. - Source: Hacker News / 5 months ago

• Elixir Livebook is a secret weapon for documentation

  To ensure you do not miss this: LiveBook comes with a Vega Lite integration (https://livebook.dev/integrations -> https://livebook.dev/integrations/vega-lite/), which means you get access to a lot of visualisations out of the box, should you need that (https://vega.github.io/vega-lite/). In the same "standing on giant's shoulders" stance, you can use Explorer (see example LiveBook at... - Source: Hacker News / 11 months ago

• Observable Plot: The JavaScript library for exploratory data visualization

  Nice, would be nice to have it integrated in GitHub markdown. Looks similar to Vega or Vega-lite(https://vega.github.io/vega-lite/). Definitely as rich as D3.js but gets the job done for simple visualisations. - Source: Hacker News / about 1 year ago