
GitHub Personal Website Generator
vscode.dev
GitLab Pages
StackBlitz
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goodprofile{me}
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Plotly
D3.js
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Highcharts
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GitHub Personal Website Generator
PlotlyPlotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.
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Based on our record, Plotly should be more popular than GitHub Personal Website Generator. It has been mentiond 34 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.
The GitHub code editor (immediately accessible by changing the ".com" to ".dev" in your browser URL, in case you didn't know) is miles, leagues ahead of what AWS has to offer. It has a full, working version of vscode.dev, which is pretty much the same as github.dev those days, I hear. It will allow you to install supported extensions, do some code completion, run your testsโ-โand even has a shell! You can't... - Source: dev.to / over 1 year ago
It'll be interesting to see how things evolve over time though โ with https://github.dev/github/dev it seems like Github is trending towards trying to solve similar problems as Vercel or Replit. - Source: Hacker News / over 3 years ago
The browser version of VS Code offered by Github is actually better than Xcode in a lot of ways. Apple should find this situation supremely embarrassing. I'm sure the engineers who work on Xcode know that it's completely fucked, but their higher-ups don't give them the resources needed to actually fix it. Source: over 3 years ago
How is made https://github.dev/github/dev without microsoft loyalities/copyright agreement? thx. Source: almost 4 years ago
Swap .com with .dev in the URL. For example, this repo https://github.com/github/dev becomes http://github.dev/github/dev. Source: almost 4 years ago
Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / 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 / about 2 years ago
vscode.dev - Now when you go to https://vscode.dev, you'll be presented with a lightweight version of VS Code running fully in the browser.
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.
GitLab Pages - GitLab Pages you can create static websites for your GitLab projects, groups, or user accounts.ย
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
StackBlitz - Online VS Code Editor for Angular and React
Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.