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Minitab 18 VS Plotly

Compare Minitab 18 VS Plotly and see what are their differences

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

Minitab 18 logo Minitab 18

Get started with Minitab, get help using Minitab tools and features, and find definitions for common terms.

Plotly logo Plotly

Low-Code Data Apps
  • Minitab 18 Landing page
    Landing page //
    2022-11-10
  • Plotly Landing page
    Landing page //
    2023-07-31

Minitab 18 features and specs

  • User-Friendly Interface
    Minitab 18 provides an intuitive, user-friendly interface that simplifies statistical analysis, making it accessible even for beginners.
  • Comprehensive Statistical Tools
    The software offers a wide range of statistical tools and processes, including regression analysis, ANOVA, and control charts, which cater to various analytical needs.
  • Quality Improvement Features
    Minitab 18 includes features specifically designed for quality improvement projects, such as Six Sigma, which are valuable for industrial applications.
  • Data Management
    Minitab allows efficient handling and manipulation of large datasets, making it suitable for complex data analysis tasks.
  • Graphical Capabilities
    The software provides robust graphical capabilities for visualizing data, which aids in better interpretation and presentation of results.

Possible disadvantages of Minitab 18

  • Cost
    Minitab is a premium software with significant licensing fees, which can be a downside for small businesses or individual users with limited budgets.
  • Limited Customization
    While Minitab offers comprehensive tools, it lacks the customization flexibility available in some other statistical software, which may be limiting for advanced users.
  • Learning Curve for Advanced Features
    Although it is user-friendly, mastering Minitabโ€™s advanced statistical features can require significant effort and training.
  • Compatibility Issues
    There might be compatibility issues with files from other statistical software, which can complicate workflows for users who rely on multiple analysis tools.

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.

Minitab 18 videos

+ Add

Crear Diagrama Causa - Efecto (Diagrama de Ishikawa) en Minitab 18 | Herramientas de calidad

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

Category Popularity

0-100% (relative to Minitab 18 and Plotly)

Minitab 18

Plotly

Numerical Computation
100 100%
Numerical Computation
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Technical Computing
100 100%
Technical Computing
0% 0
Charting Libraries
0 0%
Charting Libraries
100% 100

User comments

Share your experience with using Minitab 18 and Plotly. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Minitab 18 and Plotly

Minitab 18 Reviews

We have no reviews of Minitab 18 yet.
Be the first one to post

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

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.

Minitab 18 mentions (0)

We have not tracked any mentions of Minitab 18 yet. Tracking of Minitab 18 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 / 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

What are some alternatives?

When comparing Minitab 18 and Plotly, you can also consider the following products

IBM SPSS Statistics - IBM SPSS Statistics is software that provides detailed analysis of statistical data. The company behind the product practically needs no introduction, as it's been a staple of the technology industry for over 100 years.

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.

RStudio - RStudioโ„ข is a new integrated development environment (IDE) for R.

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

Stata - Stata is a software that combines hundreds of different statistical tools into one user interface. Everything from data management to statistical analysis to publication-quality graphics is supported by Stata. Read more about Stata.

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.

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