Plotly VS Repohistory
Compare Plotly VS Repohistory and see what are their differences
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Plotly
D3.js
RAWGraphs
Tableau
Google Charts
Highcharts
Bokeh
Chart.js
Repohistory
RepoTracker
GitHub
Repobeats
Trackgit
As a maintainer of a few open-source projects, Iโve always wanted to better understand the traffic sources and trends for my repos. Unfortunately, GitHubโs built-in analytics only show limited data from the past 14 days, which doesnโt provide much insight.
Thatโs why I built Repohistory, a better GitHub repo analytics platform. It automatically fetches and stores your traffic data every day, so youโre no longer limited to just 14 days. The dashboard shows you:
So if you have any public repos on GitHub, Repohistory can give you a much clearer picture of your traffic trends.
Try it here: https://repohistory.com
Plotly RepohistoryNo features have been listed yet.
Plotly 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 seems to be more popular. 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.
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 / 5 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
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.
RepoTracker - Better GitHub repository stats and insights
RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...
GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.
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.
Repobeats - Stunning insights for your GitHub Repo