Software Alternatives, Accelerators & Startups

F# VS Plotly

Compare F# VS Plotly and see what are their differences

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F# logo F#

F# is a mature, open source, cross-platform, functional-first programming language.

Plotly logo Plotly

Low-Code Data Apps
  • F# Landing page
    Landing page //
    2021-09-15

We recommend LibHunt F# for discovery and comparisons of trending F# projects.

  • Plotly Landing page
    Landing page //
    2023-07-31

F# features and specs

  • Functional Programming Paradigm
    F# primarily supports functional programming, which promotes immutability and first-class functions, leading to more predictable and maintainable code.
  • Interoperability
    F# provides seamless interoperability with .NET libraries and languages like C#, allowing developers to leverage a vast ecosystem of tools and libraries.
  • Conciseness
    F# code tends to be concise and expressive, reducing boilerplate code and enhancing readability.
  • Type Inference
    Powerful type inference capabilities reduce the need for explicit type annotations, making the code easier to write and refactor.
  • Asynchronous Programming
    F# provides robust support for asynchronous programming, enabling the creation of responsive applications and efficient I/O handling.
  • Community and Resources
    An active community and wealth of online resources provide support and facilitate learning through forums, tutorials, and documentation.
  • Multi-Paradigm
    Despite its functional core, F# also supports imperative and object-oriented programming, offering flexibility to developers.

Possible disadvantages of F#

  • Learning Curve
    For developers coming from imperative or object-oriented backgrounds, the functional programming paradigm in F# can present a steep learning curve.
  • IDE and Tooling
    Although F# is integrated into Visual Studio, the overall tooling and IDE support for F# is not as mature as for more established languages like C#.
  • Market Demand
    The demand for F# skillsets in the job market is comparatively lower than for more mainstream languages, potentially affecting career opportunities.
  • Performance Overhead
    While generally efficient, certain operations in F# may incur performance overhead due to the functional aspects and abstractions, especially when not optimized.
  • Library Support
    Although F# can access the .NET library ecosystem, it has a relatively smaller number of libraries and frameworks specifically designed for it compared to languages like Python or JavaScript.
  • Niche Language
    F# is often considered a niche language, which can lead to a smaller community and fewer resources compared to more popular languages.

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 F#

Overall verdict

  • F# is particularly well-regarded in areas such as financial computing, data analysis, scientific computing, and machine learning. Its ability to combine functional programming paradigms with .NET's powerful libraries and tools provides a versatile environment for both small and large projects. However, it might not be the best fit for developers who are not familiar with functional programming or are working in domains where F# lacks extensive libraries compared to other languages like Python or JavaScript.

Why this product is good

  • F# is a functional-first programming language that runs on the .NET platform. It emphasizes immutability and concise code, making it suitable for complex data processing, reactive programming, and quick prototyping. F# has strong support for parallel and asynchronous programming, which helps in efficiently utilizing multi-core processors.

Recommended for

  • Data Scientists
  • Financial Analysts
  • Developers seeking high-performance applications
  • Functional programming enthusiasts
  • Teams using the .NET ecosystem looking for a concise and expressive language.

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.

F# videos

F# Software Foundation Year in Review

More videos:

  • Review - F# Blues Harp Review
  • Review - F# base Bhavika flute review by Dhyey patel ji

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 F# and Plotly)
Programming Language
100 100%
0% 0
Data Visualization
0 0%
100% 100
OOP
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 F# and Plotly

F# 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.
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 should be more popular than F#. 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.

F# mentions (22)

  • Solving the NY Times "Pips" game with F#
    We'll use F# to implement this algorithm because functional programming is a good choice for "black box" problems like this that have no side-effects, and .NET is an easy, fast platform to work with. (F# is actually a great all-purpose language for just about anything, but I digress.). - Source: dev.to / 11 months ago
  • What's New in F# 9
    It's an open-source project with its own F# Software Foundation. If Microsoft drops it, I think it would continue. https://fsharp.org/. - Source: Hacker News / almost 2 years ago
  • Rust panics under the hood, and implementing them in .NET
    Before Rich made Clojure for the JVM, he wrote dotLisp[1] for the CLR. Not long after Clojure was JVM hosted, it was also CLR hosted[2]. One of my first experiences with ML was F#[3], a ML variant that targets the CLR. These all predate the MIT licensed .net, but prior to that there was mono, which was also MIT licensed. 1: https://dotlisp.sourceforge.net/dotlisp.htm 2: https://github.com/clojure/clojure-clr. - Source: Hacker News / almost 2 years ago
  • Roc – A fast, friendly, functional language
    Oh yeah. A key hindrance of F# is that MS treats it like a side project even though it's probably their secret weapon, and a lot of the adopters are dotnet coders who already know the basics so the on-boarding is less than ideal. https://fsharp.org/ is the best place to actually start. https://fsharpforfunandprofit.com/ is the standard recommendation from there but there's finally some good youtube and other... - Source: Hacker News / almost 3 years ago
  • Building React Components Using Unions in TypeScript
    Naturally I’d recommend using a better language such as ReScript or Elm or PureScript or F#‘s Fable + Elmish, but “React” is the king right now and people perceive TypeScript as “less risky” for jobs/hiring, so here we are. - Source: dev.to / almost 3 years ago
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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 F# and Plotly, you can also consider the following products

Clojure - Clojure is a dynamic, general-purpose programming language, combining the approachability and interactive development of a scripting language with an efficient and robust infrastructure for multithreaded programming.

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.

Elixir - Dynamic, functional language designed for building scalable and maintainable applications

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

C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation

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.