Software Alternatives, Accelerators & Startups

React D3 Library VS Plotly

Compare React D3 Library VS Plotly and see what are their differences

React D3 Library logo React D3 Library

The easiest way to use D3.js in React

Plotly logo Plotly

Low-Code Data Apps
  • React D3 Library Landing page
    Landing page //
    2019-04-11
  • Plotly Landing page
    Landing page //
    2023-07-31

React D3 Library features and specs

  • Integration
    React D3 Library allows for seamless integration of D3 visualizations within React components, making it easier to manage and update large-scale visualizations within a React application.
  • Component-Based Architecture
    By utilizing React's component-based architecture, this library can help structure D3 visualizations in a modular and reusable way, improving the maintainability of projects.
  • Declarative Approach
    React's declarative programming style can simplify the complexity of managing state and component lifecycle, especially for dynamic D3 visualizations.

Possible disadvantages of React D3 Library

  • Performance Overhead
    Integrating D3 visualizations within React components can introduce a performance overhead because React has its own rendering cycle, which might conflict with D3's direct DOM manipulations.
  • Learning Curve
    Developers need to understand both React and D3 paradigms, which can be challenging, especially when dealing with complex data visualizations.
  • Limited Community Support
    Compared to libraries like React-Vis or Victory, the React D3 Library may have less community support and fewer resources, which could be a limitation for developers seeking help and examples.

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.

React D3 Library 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 React D3 Library and Plotly)
Charting Libraries
9 9%
91% 91
Data Visualization
5 5%
95% 95
Data Dashboard
8 8%
92% 92
Javascript UI Libraries
13 13%
87% 87

User comments

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Reviews

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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 thatโ€™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 React D3 Library. While we know about 34 links to Plotly, we've tracked only 3 mentions of React D3 Library. 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.

React D3 Library mentions (3)

  • Can someone show me how to do this in React or point me to a tutorial?
    There are d3 wrappers for React that might work. Something like this: https://react-d3-library.github.io/. Source: almost 4 years ago
  • console.log(':(')
    Today is rare to find something that doesn't exist in react ecosystem. If you want to use D3 probably you will use this: https://react-d3-library.github.io/. Source: about 4 years ago
  • anyone tried nvd3 in react? I need a stacked area chart and like theirs
    Check this: https://react-d3-library.github.io/. Source: almost 5 years ago

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    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
  • 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 / over 1 year 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 / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!๐Ÿค“
    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
  • 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 2 years ago
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What are some alternatives?

When comparing React D3 Library and Plotly, you can also consider the following products

Highcharts - A charting library written in pure JavaScript, offering an easy way of adding interactive charts to your web site or web application

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.

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

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

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.

Google Charts - Interactive charts for browsers and mobile devices.