Software Alternatives, Accelerators & Startups
Register | Login

Plotly VS Google Charts

Compare Plotly VS Google Charts and see what are their differences

BusinessXray
Automated 60-second forensic business auditing pipeline powered by OpenAI Nano AI. Built for consultants and analysts. featured
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Plotly logo Plotly

Low-Code Data Apps

Google Charts logo Google Charts

Interactive charts for browsers and mobile devices.
  • Plotly Landing page
    Landing page //
    2023-07-31
  • Google Charts Landing page
    Landing page //
    2023-05-10

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.

Google Charts features and specs

  • Easy Integration
    Google Charts can be easily integrated with web applications by adding a simple script tag and using JavaScript for customization.
  • Wide Variety of Chart Types
    Google Charts supports a wide range of chart types including line charts, bar charts, pie charts, and more, allowing for comprehensive data visualization.
  • Dynamic Data Handling
    The library allows for dynamic data handling and real-time updates, enabling interactive and responsive charts.
  • Cross-Browser Compatibility
    Google Charts is compatible with most modern browsers, ensuring a consistent experience across different platforms.
  • Customizable
    Offers extensive customization options such as modifying colors, labels, and tooltips, which allows developers to tailor visualizations to their specific needs.
  • Free to Use
    Google Charts is free to use, making it an appealing choice for developers looking for cost-effective data visualization solutions.
  • Comprehensive Documentation
    Provides extensive documentation and tutorials, which helps developers to quickly get started and resolve issues efficiently.

Possible disadvantages of Google Charts

  • Dependency on Google
    Requires an internet connection to fetch the Google Charts library, and performance can be affected if there are connectivity issues.
  • Limited Customization Compared to Alternatives
    Though customizable, it has fewer options and flexibility compared to other libraries like D3.js, which might be a limitation for advanced users.
  • Load Time
    The initial loading time of Google Charts can be slower compared to lightweight charting libraries due to the need to retrieve data from Google's servers.
  • Security Concerns
    As it relies on loading scripts from Google's servers, there might be security concerns in highly sensitive applications.
  • Not Open Source
    Google Charts is not open source, which might be a barrier for developers who prefer open-source solutions for greater control and transparency.
  • Limited Offline Support
    Static charts cannot be easily generated without an internet connection, limiting its use in offline applications.

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.

Analysis of Google Charts

Overall verdict

  • Google Charts is a highly recommended option for anyone seeking a robust, versatile, and free charting library. It combines ease of use with advanced capabilities, making it suitable for both beginners and experienced developers.

Why this product is good

  • Google Charts is a powerful and flexible tool for creating a variety of charts and graphs easily. It is well-suited for both simple and complex data visualizations, offering a wide selection of chart types. Moreover, it integrates smoothly with web applications and is highly customizable, allowing users to adjust the look and functionality to fit specific needs. The documentation provided by Google is extensive and helps users to quickly set up and utilize the tool effectively.

Recommended for

  • Web developers looking to add charts to their websites
  • Data analysts needing to visualize complex datasets
  • Business users seeking to create interactive dashboards
  • Educators and students who require data visualization for projects and presentations

Plotly videos

+ Add

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

Google Charts videos

+ Add

Data Visualization for the Web Using Google Charts

More videos:

  • Review - Incorporating Google Charts in a FileMaker Solution | FileMaker Training
  • Review - Google Charts for Native Android Apps

Category Popularity

0-100% (relative to Plotly and Google Charts)

Plotly

Google Charts

Data Visualization
51 51%
Data Visualization
49% 49
Data Dashboard
40 40%
Data Dashboard
60% 60
Charting Libraries
48 48%
Charting Libraries
52% 52
Javascript UI Libraries
100 100%
Javascript UI Libraries
0% 0

User comments

Share your experience with using Plotly and Google Charts. 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 Plotly and Google Charts

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.
Source: www.technotification.com
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...
Source: www.geeksforgeeks.org
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.
Source: blog.logrocket.com

Google Charts Reviews

15 JavaScript Libraries for Creating Beautiful Charts
Google Charts also comes with various customization options that help in changing the look of the graph. Charts are rendered using HTML5/SVG to provide cross-browser compatibility and cross-platform portability to iPhones, iPads, and Android. It also includes VML for supporting older IE versions.
Source: www.sitepoint.com
Top 10 JavaScript Charting Libraries for Every Data Visualization Need
Google Charts is an excellent choice for projects that do not require complicated customization and prefer simplicity and stability.
Source: hackernoon.com
A Complete Overview of the Best Data Visualization Tools
Google Charts is a powerful, free data visualization tool that is specifically for creating interactive charts for embedding online. It works with dynamic data and the outputs are based purely on HTML5 and SVG, so they work in browsers without the use of additional plugins. Data sources include Google Spreadsheets, Google Fusion Tables, Salesforce, and other SQL databases.
Source: www.toptal.com
The Best Data Visualization Tools - Top 30 BI Software
Google Charts runs on SVG and HTML5, aiming for Android, iOS and total cross-browser compatibility, including older versions of Internet Explorer. All of the charts you can create are interactive and you may be able zoom in on some of them. The site offers a fairly comprehensive gallery where you can find a variety of types of visualizations and interactions that you can use.
Source: improvado.io

Social recommendations and mentions

Based on our record, Plotly should be more popular than Google Charts. 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.

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
View more

Google Charts mentions (10)

  • The top 11 React chart libraries for data visualization
    This library leverages the robustness of Googleโ€™s chart tools combined with a React-friendly experience. It is ideal for developers familiar with Googleโ€™s visualization ecosystem. - Source: dev.to / almost 3 years ago
  • Using Images in a chart?
    I tried adding the images as labels and it didn't work. If this is possible at all, it would probably require Google Charts. Source: over 3 years ago
  • What are some good graph visualization libraries?
    Google's is a bit simpler to work with but more basic in terms of features https://developers.google.com/chart. Source: over 3 years ago
  • 5 Best Free JS Chart Libraries
    Google charts Https://developers.google.com/chart. - Source: dev.to / almost 4 years ago
  • Suggestions for super simple QR code generator
    I did find a nice solution for Access forms where you can use a web browser control and developers.google.com/chart to render a QR code in that control based on the contents of other controls (textboxes, comboboxes, etc.,.). This would be perfect if it didn't a) rely on an active WAN connection and b) rely on that specific URL being active indefinitely. Source: about 4 years ago
View more

What are some alternatives?

When comparing Plotly and Google Charts, you can also consider the following products

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...

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

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.

Whatagraph - Whatagraph is the most visual multi-source marketing reporting platform. Built in collaboration with digital marketing agencies

Bokeh - Bokeh visualization library, documentation site.

Loading...