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Jupyter VS Google Charts

Compare Jupyter VS Google Charts and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Jupyter logo Jupyter

Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.

Google Charts logo Google Charts

Interactive charts for browsers and mobile devices.
  • Jupyter Landing page
    Landing page //
    2023-06-22
  • Google Charts Landing page
    Landing page //
    2023-05-10

Jupyter features and specs

  • Interactive Computing
    Jupyter allows real-time interaction with the data and code, providing immediate feedback and making it easier to experiment and iterate.
  • Rich Media Output
    It supports output in various formats including HTML, images, videos, LaTeX, and more, enhancing the ability to visualize and interpret results.
  • Language Agnostic
    Jupyter supports multiple programming languages through its kernel system (e.g., Python, R, Julia), allowing flexibility in the choice of tools.
  • Collaborative Features
    It enables collaboration through shared notebooks, version control, and platform integrations like GitHub.
  • Educational Tool
    Jupyter is widely used for teaching, thanks to its easy-to-use interface and ability to combine narrative text with code, making it ideal for assignments and tutorials.
  • Extensibility
    Jupyter is highly extensible with a large ecosystem of plugins and extensions available for various functionalities.

Possible disadvantages of Jupyter

  • Performance Issues
    For larger datasets and more complex computations, Jupyter can be slower compared to running scripts directly in a dedicated IDE.
  • Version Control Challenges
    Managing version control for Jupyter notebooks can be cumbersome, as they are not plain text files and include metadata that can make diffing and merging complex.
  • Resource Intensive
    Running Jupyter notebooks can be resource-intensive, especially when working with multiple large notebooks simultaneously.
  • Security Concerns
    Because Jupyter allows code execution in the browser, it can be a potential security risk if notebooks from untrusted sources are run without restrictions.
  • Dependency Management
    Managing dependencies and ensuring that the notebook runs consistently across different environments can be challenging.
  • Less Suitable for Production
    Jupyter is often considered more as a research and educational tool rather than a production environment; transitioning from a notebook to production code can require significant refactoring.

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 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

Jupyter videos

+ Add

What is Jupyter Notebook?

More videos:

  • Tutorial - Jupyter Notebook Tutorial: Introduction, Setup, and Walkthrough
  • Review - JupyterLab: The Next Generation Jupyter Web Interface

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 Jupyter and Google Charts)

Jupyter

Google Charts

Data Science And Machine Learning
100 100%
Data Science And Machine Learning
0% 0
Data Dashboard
47 47%
Data Dashboard
53% 53
Data Visualization
0 0%
Data Visualization
100% 100
Database Tools
100 100%
Database Tools
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Jupyter and Google Charts

Jupyter Reviews

Jupyter Notebook & 10 Alternatives: Data Notebook Review [2023]
Once you install nteract, you can open your notebook without having to launch the Jupyter Notebook or visit the Jupyter Lab. The nteract environment is similar to Jupyter Notebook but with more control and the possibility of extension via libraries like Papermill (notebook parameterization), Scrapbook (saving your notebook’s data and photos), and Bookstore (versioning).
Source: lakefs.io
7 best Colab alternatives in 2023
JupyterLab is the next-generation user interface for Project Jupyter. Like Colab, it's an interactive development environment for working with notebooks, code, and data. However, JupyterLab offers more flexibility as it can be self-hosted, enabling users to use their own hardware resources. It also supports extensions for integrating other services, making it a highly...
Source: deepnote.com
12 Best Jupyter Notebook Alternatives [2023] – Features, pros & cons, pricing
Jupyter Notebook is a widely popular tool for data scientists to work on data science projects. This article reviews the top 12 alternatives to Jupyter Notebook that offer additional features and capabilities.
Source: noteable.io
15 data science tools to consider using in 2021
Jupyter Notebook's roots are in the programming language Python -- it originally was part of the IPython interactive toolkit open source project before being split off in 2014. The loose combination of Julia, Python and R gave Jupyter its name; along with supporting those three languages, Jupyter has modular kernels for dozens of others.
Source: searchbusinessanalytics.techtarget.com
Top 4 Python and Data Science IDEs for 2021 and Beyond
Yep — it’s the most popular IDE among data scientists. Jupyter Notebooks made interactivity a thing, and Jupyter Lab took the user experience to the next level. It’s a minimalistic IDE that does the essentials out of the box and provides options and hacks for more advanced use.
Source: towardsdatascience.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, Jupyter seems to be a lot more popular than Google Charts. While we know about 216 links to Jupyter, we've tracked only 10 mentions of Google Charts. 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.

Jupyter mentions (216)

  • The 3 Best Python Frameworks To Build UIs for AI Apps
    Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / 2 months ago
  • LangChain: From Chains to Threads
    LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 3 months ago
  • Applied Artificial Intelligence & its role in an AGI World
    Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 5 months ago
  • Jupyter Notebook for Java
    Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 9 months ago
  • JIRA Analytics with Pandas
    One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 12 months ago
View more

Google Charts mentions (10)

  • The top 11 React chart libraries for data visualization
    This library leverages the robustness of Google’s chart tools combined with a React-friendly experience. It is ideal for developers familiar with Google’s visualization ecosystem. - Source: dev.to / over 1 year 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: about 2 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 2 years ago
  • 5 Best Free JS Chart Libraries
    Google charts Https://developers.google.com/chart. - Source: dev.to / over 2 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: almost 3 years ago
View more

What are some alternatives?

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

Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.

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

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

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.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

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

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