Software Alternatives, Accelerators & Startups

Clippy - CSS Clip-path Maker VS Plotly

Compare Clippy - CSS Clip-path Maker VS Plotly and see what are their differences

Clippy - CSS Clip-path Maker logo Clippy - CSS Clip-path Maker

Drag and points to generate clip-path CSS

Plotly logo Plotly

Low-Code Data Apps
  • Clippy - CSS Clip-path Maker Landing page
    Landing page //
    2022-05-04
  • Plotly Landing page
    Landing page //
    2023-07-31

Clippy - CSS Clip-path Maker features and specs

  • User-Friendly Interface
    Clippy offers an intuitive and straightforward interface that makes it easy for users, regardless of their expertise level, to create complex clip-path shapes without needing to write code manually.
  • Real-Time Preview
    The tool provides a real-time preview of the changes as users design their clip-path shapes, allowing for immediate visual feedback and adjustments.
  • Wide Range of Shapes
    Clippy supports a variety of predefined shapes and custom paths, giving designers flexibility and creativity in their projects.
  • Ease of Integration
    Users can seamlessly integrate the generated clip-path code into their web projects, enhancing productivity and workflow efficiency.
  • No Installation Required
    Being a web-based tool, Clippy does not require any installation, enabling easy and quick access from any device with internet connectivity.

Possible disadvantages of Clippy - CSS Clip-path Maker

  • Limited to Clip-Path
    As a specialized tool focused solely on clip-path generation, Clippy does not cover other CSS functionalities, which might necessitate additional tools for comprehensive design.
  • Dependency on Internet Connectivity
    Since Clippy is an online tool, its functionality is dependent on having a stable internet connection, which could be a limitation in offline environments.
  • Learning Curve for Complex Shapes
    While the tool is user-friendly for basic shapes, creating highly complex and intricate paths might still require some learning and understanding of the underlying CSS properties.
  • Potential Performance Impact
    Complex clip-paths can have performance implications on rendering, especially in browsers or devices with limited processing power.

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.

Clippy - CSS Clip-path Maker videos

No Clippy - CSS Clip-path Maker videos yet. You could help us improve this page by suggesting one.

Add video

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 Clippy - CSS Clip-path Maker and Plotly)
Design Tools
100 100%
0% 0
Data Visualization
0 0%
100% 100
Developer Tools
100 100%
0% 0
Data Dashboard
0 0%
100% 100

User comments

Share your experience with using Clippy - CSS Clip-path Maker and Plotly. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare Clippy - CSS Clip-path Maker and Plotly

Clippy - CSS Clip-path Maker Reviews

We have no reviews of Clippy - CSS Clip-path Maker yet.
Be the first one to post

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

Plotly might be a bit more popular than Clippy - CSS Clip-path Maker. We know about 33 links to it since March 2021 and only 26 links to Clippy - CSS Clip-path Maker. 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.

Clippy - CSS Clip-path Maker mentions (26)

  • Essential CSS3 Features Every Web Developer Should Master
    Pro Tip: Use online tools like Clippy to generate clip-path values. - Source: dev.to / 4 months ago
  • 10 CSS Code Snippets Every UI Developer Should Know
    Want to create other shapes? Check out this nifty CSS shapes generator: CSS Shape Generator. - Source: dev.to / 7 months ago
  • Frontend resources! 🚀
    Clip path: Get creative with shapes using Clippy. - Source: dev.to / about 1 year ago
  • Earth rescue - A CSS only game
    In the beginning I only had buttons to click, but then I guessed I could make small icons for the ecological disasters and I found Bennett Feely's CSS clip-path maker. Altough I know Adobe Illustrator and also wrote some SVG by hand, I was lazy to figure out all the shapes and I didn't want to include any images or vector graphics at all in this project. So that website came in very handy. - Source: dev.to / about 1 year ago
  • 5 ways to style text with CSS inspired by the Spider-verse
    To create this CSS glitch animation, we used the clip-path property. You can use Bennett Feely’s Clippy tool to generate clip-path properties in any of the preset shapes or to make a custom clip-path. Ours had only four points — what if yours has eight points like a spider? - Source: dev.to / about 1 year ago
View more

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 / 2 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 / 4 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 / 6 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 / 12 months 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
View more

What are some alternatives?

When comparing Clippy - CSS Clip-path Maker and Plotly, you can also consider the following products

Glass UI Generator - CSS generator for glassmorphism

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.

CSSGradient.io - As a free css gradient generator tool, this website lets you create a colorful gradient background for your website, blog, or social media profile.

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

Tailwind Box Shadows - A curated list of box shadows for your next web project.

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