Software Alternatives & Startups

jamovi VS Plotly

Compare jamovi VS Plotly and see what are their differences

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jamovi logo jamovi

jamovi is a free and open statistical platform which is intuitive to use, and can provide the...

Plotly logo Plotly

Low-Code Data Apps
  • jamovi Landing page
    Landing page //
    2022-11-03
  • Plotly Landing page
    Landing page //
    2023-07-31

jamovi features and specs

  • User-friendly interface
    jamovi features a clean, intuitive interface that is easy to navigate, making it accessible for users with varying levels of statistical expertise.
  • Free and open-source
    jamovi is completely free and open-source, which allows users to download, use, and modify the software without any cost.
  • Integration with R
    jamovi has built-in support for R, enabling users to run R scripts and use R packages directly within the software, providing additional flexibility and functionality.
  • Regular updates
    The development team frequently releases updates to improve functionality, fix bugs, and add new features, ensuring that the software stays current and reliable.
  • Comprehensive features
    jamovi offers a wide range of statistical analyses and graphical options, catering to both basic and advanced user needs.

Possible disadvantages of jamovi

  • Limited advanced features
    While jamovi covers most basic and intermediate statistical methods, it may lack some of the more advanced statistical techniques found in other specialized software.
  • Performance issues
    Occasionally, users may experience performance issues, such as slow processing times or software crashes, especially with very large datasets.
  • Learning curve for R integration
    Although integration with R is a pro, it can also be a con, as it may require additional learning for users who are not already familiar with R programming.
  • Less established than competitors
    Compared to other statistical software like SPSS or SAS, jamovi is relatively new and may not have as extensive a user base or as many community resources.
  • Limited customer support
    As an open-source project, jamovi relies primarily on community support and forums, which may not be as responsive or comprehensive as dedicated customer support services.

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 jamovi

Overall verdict

  • Jamovi is considered good for users who need a free, intuitive, and flexible tool for statistical analysis. It is particularly appreciated for its user-friendly design and ability to meet the needs of a wide range of users, from students to researchers.

Why this product is good

  • Jamovi is an open-source statistical software that is user-friendly and designed for ease of use, making it accessible to both beginners and advanced users. It provides an intuitive interface and integrates seamlessly with R, allowing users to extend its capabilities. Jamovi includes a variety of statistical analyses and graphical representations, making it suitable for educational purposes and professional use in various fields.

Recommended for

  • Students learning statistics
  • Researchers conducting data analysis
  • Educators teaching statistical methods
  • Anyone looking for a free alternative to commercial statistical software

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.

jamovi videos

jamovi for Data Analysis - Full Tutorial

More videos:

  • Tutorial - PSYS 241: JAMOVI Tutorial 7 - Review
  • Review - Reliability analysis — jamovi
  • Tutorial - JAMOVI 📊. Un robusto software libre de estadística (🔥 2.3 ya en español)
  • Tutorial - Estadística descriptiva con Jamovi 📊 - Tutorial

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 jamovi and Plotly)
Technical Computing
100 100%
0% 0
Data Visualization
0 0%
100% 100
Business & Commerce
100 100%
0% 0
Charting Libraries
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 jamovi and Plotly

jamovi Reviews

  1. Bob Muenchen
    · Retired statistician at University of Tennessee ·
    Beautiful User Interface

    jamovi has one of the most attractive user interfaces. Even the colors used for window-dressing match the default colors for its graphs. Like JASP, its dialogs provide instant results as each item is checked off. That immediate feedback feels great! Corrections to data values are also immediately reflected in each piece of output that would be affected. However, this also means that you can't do one step, restructure the data, then do another since jamovi requires each step to have the same data structure. SPSS, Minitab, BlueSky Statistics, and JMP can all do such common data-wrangling tasks. So, if you restructure your data a lot, you'll need to do that with another tool and read the data in separately for each structure. jamovi's menus start out very sparse and you extend them by downloading needed parts later. This is the opposite of similar tools like SPSS, Minitab, and BlueSky Statistics, which show all their capabilities upon installation. That makes it good for beginners who avoid the others' complex menus. Regarding analytic methods, jamovi has the most popular statistics. The main topics it lacks are quality control and machine learning/AI. Also, it cannot save models for making predictions on a different dataset.

    Pros:    Ui is very attractive|Feedbacks
    Cons:    Limited features

Free statistics software for Macintosh computers (Macs)
Other notes. Developer Jonathon Love pointed us to the Jamovi library of extra procedures. A long, well-illustrated Jamovi blog post also goes over the fine graphics capabilities within Jamovi, which PSPP can only dream of. In our run-throughs, the numbers were identical to SPSS, PSPP, and JASP.
10 Best Free and Open Source Statistical Analysis Software
Jamovi is a free and open source statistical software built on ‘R' language. Intuitive interface, quality spreadsheet, optimized analysis are the key reasons for its popularity. It performs all statistical tests with reliability and competence.

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 more popular. 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.

jamovi mentions (0)

We have not tracked any mentions of jamovi yet. Tracking of jamovi recommendations started around Mar 2021.

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 / 6 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!🤓
    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 / almost 2 years 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 jamovi and Plotly, you can also consider the following products

JASP - JASP, a low fat alternative to SPSS, a delicious alternative to R.

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.

Statista - The Statistics Portal for Market Data, Market Research and Market Studies

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

Montecarlito - MonteCarlito is a free Excel-add-in to do Monte-Carlo-simulations.

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.