Software Alternatives & Startups

Plotly VS JASP

Compare Plotly VS JASP and see what are their differences

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Plotly logo Plotly

Low-Code Data Apps

JASP logo JASP

JASP, a low fat alternative to SPSS, a delicious alternative to R.
  • Plotly Landing page
    Landing page //
    2023-07-31
  • JASP Landing page
    Landing page //
    2023-05-08

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.

JASP features and specs

  • User-Friendly Interface
    JASP offers an intuitive and visually appealing interface that is easy for users to navigate, making statistical analysis accessible even to those who are not heavily experienced in statistics.
  • Open Source
    Being open-source, JASP is available for free, enabling anyone to use it without financial barriers and allowing for community-driven improvements and customizations.
  • Bayesian Methods
    JASP includes a wide array of Bayesian statistical tools, providing advanced options for users interested in Bayesian inference, which is often not as well-supported in other statistical software.
  • Integration with R
    JASP allows for integration with R, providing flexibility for users who wish to perform more customized or complex analyses by incorporating R scripts within the user-friendly JASP environment.
  • Dynamic Reports
    The software enables users to generate dynamic reports that update in real-time as data changes, streamlining the reporting process and making it easier to share findings.

Possible disadvantages of JASP

  • Limited Customization
    While JASP provides a great user interface and many built-in options, it offers less customization and fewer advanced features compared to more flexible software like R or Python.
  • Performance Issues with Large Data Sets
    JASP may struggle with performance issues when handling extremely large datasets, potentially causing delays or crashes during analysis.
  • Dependence on Internet Connection for Some Features
    Some of JASP's functionalities rely on an active internet connection, which can be limiting in situations where such a connection is unreliable or unavailable.
  • Limited Support for Complex Data Manipulation
    JASP is not designed for extensive data manipulation or cleaning tasks, requiring users to preprocess their data using other tools before importing it into JASP for analysis.
  • Relatively New Software
    As a newer entrant in the field of statistical software, JASP lacks the extensive user base and comprehensive third-party resources available for more established software platforms.

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 JASP

Overall verdict

  • JASP is considered a good tool for statistical analysis, especially for educational purposes and for those who need a cost-effective solution that doesn’t sacrifice functionality.

Why this product is good

  • JASP is appreciated for its user-friendly interface, open-source nature, and powerful statistical analysis capabilities. It provides an easy transition for those familiar with SPSS but looking for a free alternative. JASP supports both frequentist and Bayesian analyses, and it offers a range of visualization tools that make it easier to interpret statistical data.

Recommended for

  • Students and educators in fields requiring statistical analysis
  • Researchers who need a comprehensive, free tool for statistical tests
  • Professionals seeking an alternative to expensive statistical software
  • Anyone interested in conducting both frequentist and Bayesian analyses

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

JASP videos

Introducing JASP

More videos:

  • Review - Berkenalan dengan JASP: Software Analisis Data Gratis dan Lengkap
  • Review - Gusion Legend Skin Cosmic Gleam Review | Jasp GamIng

Category Popularity

0-100% (relative to Plotly and JASP)
Data Visualization
100 100%
0% 0
Technical Computing
0 0%
100% 100
Charting Libraries
100 100%
0% 0
Business & Commerce
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 Plotly and JASP

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.

JASP Reviews

  1. Bob Muenchen
    · Retired statistician at University of Tennessee ·
    Good choice for teaching stats

    JASP works very similarly to jamovi. That's not a coincidence, as some JASP developers split off to create jamovi. You can open a single dataset and use the most popular statistics and machine learning methods. But if you have multiple datasets to merge, you must do that in another tool. Also, the dataset must maintain a single structure throughout your analyses. Restructuring or transposing is not allowed. It is commonly said that data scientists spend 80% of their time wrangling data like that, so that's a significant limitation for general use. However, those simplifications make JASP a good choice for teaching. Another advantage for teaching is that the menus are very sparse, but you can add to them easily by downloading additional modules. That's the opposite of similar software such as BlueSky Statistics, SPSS, or Minitab, which install all features at once. If you're looking for free and open-source software, JASP and jamovi are best for teaching while BlueSky Statistics is best for general-purpose analysis.

    Competitors: BlueSky Statistics
    Pros:    Easy user interface
    Cons:    Limited features

Free statistics software for Macintosh computers (Macs)
JASP and Jamovi share lightning-fast speed; a wide range of statistics, with extra plugins on Jamovi; and easy installation on Macs, Windows, and Linux. Their basic interface has an Office 365-style open/save/print/export tab; options on the left, output on the right layout; instant changes to the output if you change the input; and export of both data and output, as...
10 Best Free and Open Source Statistical Analysis Software
Jeffreys’s Amazing Statistics Program (JASP) came into existence as a free and open source alternative to SPSS with powerful Bayesian analyses as its core feature. It has a user-friendly interface. Results are annotated with descriptive text to make analysis easy.
25 Best Statistical Analysis Software
This versatile, free, and open-source statistical software is specifically designed to cater to the needs of researchers and students. With its user-friendly interface, JASP makes data analysis and visualization more accessible and efficient.

Social recommendations and mentions

Based on our record, Plotly should be more popular than JASP. 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 / 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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JASP mentions (15)

  • Bayesian Epistemology
    For anyone looking for a quick and hands-on dive into the world of Bayesian modelling and inference, I can't recommend JASP enough, made freely available by the University of Amsterdam[0]. I've recommended it before, and it's just a breeze to work with, seeing frequentist and Bayesian analyses side-by-side. [0]: https://jasp-stats.org/. - Source: Hacker News / over 1 year ago
  • Introduction to Modern Statistics
    Anyone looking to apply and compare frequentist and bayesian methods within a unified GUI (which is essentially an elegant wrapper to R and selected/custom statistical packages), should check out JASP developed by the University of Amsterdam [0]. It's free to use, and the graphs + captions generated on each step are of publication quality out of the box. Using it truly feels like a 'fresh way' to do... - Source: Hacker News / almost 3 years ago
  • Can anyone share spss for macOS?
    Https://jasp-stats.org fully free. Its advisible to learn python, R or matlab for graduate school. Source: about 3 years ago
  • Help with my analysis in spss. I have 5 independent (ordinal) variables. 1 Moderator and 1 dependent variable. How do I run a multiple regression in SPSS?
    Also for alternative software that are much easier to use take a look at JASP or jamovi (both are very similar); and as a bonus, neither of these two will require you to manually add product variables to your dataset. Source: about 3 years ago
  • [D] Discussion: R, Python, or Excel best way to go?
    If you have no access to SPSS (or SAS, or JMP), then look into JASP (https://jasp-stats.org/). I've only just touched that. One thing I believe is that JASP (as well as JMP) will allow/block off tests and analyses depending on the nature of each column. This means that, for example, if you have groups A, ..., Z, the software will treat those as non-numbers, which can only be used as inputs for variables which... Source: over 3 years ago
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What are some alternatives?

When comparing Plotly and JASP, 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.

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

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

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

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.

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