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(R)?ex VS Plotly

Compare (R)?ex VS Plotly and see what are their differences

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

(R)?ex logo (R)?ex

(R)?ex - manage all your boxes from a central point - Datacenter Automation and Configuration...

Plotly logo Plotly

Low-Code Data Apps
  • (R)?ex Landing page
    Landing page //
    2023-05-02
  • Plotly Landing page
    Landing page //
    2023-07-31

(R)?ex features and specs

  • Simplicity
    Rex is designed to be simple and easy to use, which helps developers automate tasks without needing extensive programming knowledge.
  • Flexible Deployment
    Rex allows for flexible deployment across different servers and environments, making it adaptable to various infrastructure setups.
  • Extensibility
    Rex can be extended with additional modules and custom scripts, providing versatility in handling a wide range of automation tasks.
  • Agent-less
    Rex does not require any agent software to be installed on remote systems, reducing the management overhead for system administrators.

Possible disadvantages of (R)?ex

  • Limited Community and Support
    Compared to more popular tools, Rex has a smaller community, which can lead to limited available resources and support.
  • Learning Curve
    Although simpler than some alternatives, new users may still encounter a learning curve, especially if they are unfamiliar with Perl.
  • Less Comprehensive Documentation
    The available documentation for Rex may not be as comprehensive or up-to-date as that for more mainstream automation tools.
  • Fewer Built-in Features
    Rex may lack some of the built-in features and integrations that other, more established automation frameworks offer out of the box.

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.

(R)?ex videos

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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 (R)?ex and Plotly)

(R)?ex

Plotly

SSH
100 100%
SSH
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Tool
100 100%
Tool
0% 0
Charting Libraries
0 0%
Charting Libraries
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 (R)?ex and Plotly

(R)?ex Reviews

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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 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.
Source: blog.logrocket.com

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than (R)?ex. While we know about 34 links to Plotly, we've tracked only 2 mentions of (R)?ex. 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.

(R)?ex mentions (2)

  • Ansible vs Fabric
    Have a look on Rex - https://rexify.org, in addition to dsl like constructs it is just pure perl. It also doesn't need any dependencies on the managed host, just perl and ssh. Source: almost 5 years ago
  • Configuring netplan enabled hosts with Rex
    Since I feel that rex needs more attention, here is a small example from $work using rex. Needed to quickly reconfigure a number of Ubuntu hosts with netplan to use static ip addresses instead of DHCP. Source: over 5 years ago

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 (R)?ex and Plotly, you can also consider the following products

Python Fabric - Fabric is a Python library and command-line tool for streamlining the use of SSH for application...

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.

Ansible - Radically simple configuration-management, application deployment, task-execution, and multi-node orchestration engine

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

Mina - Really fast deployer and server automation tool

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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