Software Alternatives, Accelerators & Startups

Beautify Github Profile VS Plotly

Compare Beautify Github Profile VS Plotly and see what are their differences

Beautify Github Profile logo Beautify Github Profile

This repository helps you to have a more beautiful and attractive github profile, and you can access a set of tools and guides for beautifying your github profile.

Plotly logo Plotly

Low-Code Data Apps
  • Beautify Github Profile Landing page
    Landing page //
    2023-08-23
  • Plotly Landing page
    Landing page //
    2023-07-31

Beautify Github Profile features and specs

  • Enhanced Visual Appeal
    Beautify Github Profile provides various tools and ideas that help users make their GitHub profiles visually appealing, which can create a better first impression for potential employers or collaborators.
  • Customizability
    The project offers a wide range of customization options. Users can personalize their profiles, making them stand out by adding unique elements like badges, markdown elements, and custom sections.
  • Improved Navigation
    By organizing and highlighting key sections, Beautify Github Profile allows users to make their profiles more navigable. This helps others find information quickly and efficiently.
  • Community Engagement
    The project encourages community engagement by showcasing popular design trends and ideas, allowing users to collaborate and share their profile designs with others.

Possible disadvantages of Beautify Github Profile

  • Complexity for Beginners
    New users or those unfamiliar with GitHub or markdown may find the customization process intimidating and might struggle to apply some of the advanced features.
  • Time-Consuming
    Creating a highly customized GitHub profile can be time-consuming, especially if users are trying to implement intricate designs or a lot of information, which might detract from coding time.
  • Possible Over-Cluttering
    There's a risk of overloading the profile with too many elements, which can lead to a cluttered and confusing layout, potentially diminishing the effectiveness of a user’s profile presentation.
  • Maintenance Requirement
    As a GitHub profile evolves or as users add more projects and updates, maintaining a beautifully designed profile might require constant updates and adjustments.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    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.

Beautify Github Profile videos

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Plotly videos

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Beautify Github Profile and Plotly)
Developer Tools
100 100%
0% 0
Data Visualization
0 0%
100% 100
Web App
100 100%
0% 0
Data Dashboard
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Beautify Github Profile and Plotly

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Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than Beautify Github Profile. While we know about 33 links to Plotly, we've tracked only 1 mention of Beautify Github Profile. 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.

Beautify Github Profile mentions (1)

  • Is GitHub (or GitHub Pages) a good option for showcasing you portfolio?
    Also found this https://zzetao.github.io/awesome-github-profile/ which also listed many sample profiles along with portfolios. Source: over 2 years ago

Plotly mentions (33)

  • Python for Data Visualization: Best Tools and Practices
    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 / 3 months ago
  • Generative AI Powered QnA & Visualization Chatbot
    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 / 5 months ago
  • Build a Stock Dashboard in less than 40 lines of Python code!🤓
    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 / 7 months ago
  • 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 / about 1 year 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: over 1 year ago
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What are some alternatives?

When comparing Beautify Github Profile and Plotly, you can also consider the following products

Git Story - Tell the story of your Git project by creating video animations (.mp4) of your commit history directly from your Git repo.

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.

Github Profile Visualizer - Tool for visualizing GitHub profiles

Chart.js - Easy, object oriented client side graphs for designers and developers.

CodersRank - The Ultimate Profile For Developers | Turn Your Code Into Your Digital Developer Profile & Get Hired Faster

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...