Software Alternatives, Accelerators & Startups

Plotly VS Vim-Plug

Compare Plotly VS Vim-Plug and see what are their differences

Plotly logo Plotly

Low-Code Data Apps

Vim-Plug logo Vim-Plug

:hibiscus: Minimalist Vim Plugin Manager. Contribute to junegunn/vim-plug development by creating an account on GitHub.
  • Plotly Landing page
    Landing page //
    2023-07-31
  • Vim-Plug Landing page
    Landing page //
    2023-09-30

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.

Vim-Plug features and specs

  • User-Friendly Syntax
    Vim-Plug uses a simple, concise syntax for plugin management which makes it easy to add, update, and remove plugins.
  • Parallel Installation
    Vim-Plug supports parallel installation of plugins, which significantly speeds up the process of setting up and updating plugins.
  • On-Demand Loading
    It provides the ability to defer loading of plugins until they are actually required, which can improve startup time and overall performance.
  • Extensive Documentation
    Vim-Plug is well-documented with a detailed guide and plenty of examples, making it easier for new users to get started.
  • Partial and Lazy Plugin Support
    Supports loading of plugins only when specific commands are invoked or files are opened, optimizing resource usage.

Possible disadvantages of Vim-Plug

  • Vim-Only
    Vim-Plug is designed specifically for Vim and Neovim, making it unsuitable for users of different text editors.
  • Manual Configuration
    While flexible, users need to manually configure their `vimrc` to manage plugins, which might be daunting for beginners.
  • Dependency Management
    Vim-Plug does not have built-in support for handling plugin dependencies, which means users must manually manage dependencies.
  • Conflict Resolution
    There are no advanced features for resolving conflicts between plugins, requiring users to manually troubleshoot issues.
  • Plugin Removal
    While Vim-Plug can remove plugins from the listing, residual files and configurations might still remain, requiring additional cleaning steps.

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 Vim-Plug

Overall verdict

  • Vim-Plug is considered a good plugin manager for Vim due to its speed, ease of use, and active maintenance. It is widely used in the Vim community and is favored for its straightforward setup and efficient plugin management.

Why this product is good

  • Vim-Plug is a minimalist and highly efficient plugin manager for Vim, known for its speed and simplicity. It allows users to easily install, update, and remove plugins with concise commands. Its asynchronous installation feature makes managing plugins faster and does not block the usage of Vim. The minimal configuration and user-friendly syntax make it accessible for both new and experienced Vim users.

Recommended for

  • Developers using Vim who want a simple and fast way to manage plugins.
  • Users looking for asynchronous plugin management in Vim.
  • Vim enthusiasts who appreciate minimalistic configurations.

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

Vim-Plug videos

Why and How I Use Vim-Plug to Manage My Vim Plugins

Category Popularity

0-100% (relative to Plotly and Vim-Plug)
Data Visualization
100 100%
0% 0
Text Editors
0 0%
100% 100
Data Dashboard
100 100%
0% 0
Software Development
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 Vim-Plug

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.

Vim-Plug Reviews

We have no reviews of Vim-Plug yet.
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Social recommendations and mentions

Based on our record, Vim-Plug should be more popular than Plotly. It has been mentiond 95 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 (33)

  • 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 / 3 months 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 / 5 months 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 / 7 months 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 1 year ago
  • Python equivalent to power bi/power query?
    For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
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Vim-Plug mentions (95)

  • How to Setup Vim for Kotlin Development
    Some examples are vim-plug, vundle, or, lazy.nvim. - Source: dev.to / 6 months ago
  • Lite 🚀 ApolloNvim Distro 2024
    👉 If you are missing a plugin, you can easily install or uninstall it using vim.plug. For more information, please visit vim.plug on GitHub or I'd be happy to advise you see about us. - Source: dev.to / 8 months ago
  • I a Avid Vim User, Finally Migrated to Neovim! How does it work, what do I gain from it?
    I have been talking about plugins since the beginning of the article, but using a simple editor doesn't involve doing everything by hand. So I have been using a plugin manager for a long time and if you don't, I strongly advise you to get started: it's very practical. I used Vim plug which was everything I like: simple and effective. - Source: dev.to / 12 months ago
  • How to use vim-plug with init.lua? win11
    Is it possible to use vim-plug with init.lua? https://github.com/junegunn/vim-plug. Source: over 1 year ago
  • Vimtex not loading (vim-plug)
    Did you really install VimTeX? Did you run :PlugInstall? Ensure you installed and set up vim-plug correctly (https://github.com/junegunn/vim-plug). If VimTeX is installed, it should be installed to '~/.vim/plugged', thus you can open a terminal, then cd ~/.vim/plugged/vimtex and you should find the files there. Source: almost 2 years ago
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What are some alternatives?

When comparing Plotly and Vim-Plug, 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.

Vim Awesome - Awesome Vim plugins from across the universe

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

Kite - Kite helps you write code faster by bringing the web's programming knowledge into your editor.

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

Neovim - Vim's rebirth for the 21st century