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ListenBrainz VS Plotly

Compare ListenBrainz VS Plotly and see what are their differences

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ListenBrainz logo ListenBrainz

Open source music website that allows users to import their listen history.

Plotly logo Plotly

Low-Code Data Apps
  • ListenBrainz Landing page
    Landing page //
    2023-06-10
  • Plotly Landing page
    Landing page //
    2023-07-31

ListenBrainz features and specs

  • Open Source
    ListenBrainz is an open-source platform, allowing users to contribute to its development and improvement.
  • Privacy-Focused
    The platform emphasizes user privacy by allowing anonymity and providing transparency about collected data.
  • Community Driven
    As part of the MetaBrainz Foundation, ListenBrainz benefits from a community-driven approach, encouraging collaboration and innovation.
  • Integration with MusicBrainz
    It integrates seamlessly with MusicBrainz, providing enriched data insights and comprehensive music metadata.
  • Data Export
    Users can export their listening data, offering flexibility in how they handle their music listening history.

Possible disadvantages of ListenBrainz

  • Less Mainstream Integration
    Compared to other music tracking services, ListenBrainz might have limited integration with popular music streaming platforms.
  • Complex Setup
    Some users might find the setup process and integration with their existing music players non-intuitive or complex.
  • Limited Standalone Features
    On its own, ListenBrainz may lack some features users expect from more comprehensive music analytics services.
  • Smaller User Base
    The platform might have a smaller community of users compared to more established commercial music services, which could impact social features.

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.

ListenBrainz videos

No ListenBrainz videos yet. You could help us improve this page by suggesting one.

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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 ListenBrainz and Plotly)

ListenBrainz

Plotly

Music Streaming
100 100%
Music Streaming
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Music
100 100%
Music
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 ListenBrainz and Plotly

ListenBrainz Reviews

We have no reviews of ListenBrainz yet.
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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

ListenBrainz might be a bit more popular than Plotly. We know about 47 links to it since March 2021 and only 34 links to Plotly. 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.

ListenBrainz mentions (47)

  • I archived 10 years of memories using Spotify
    Https://listenbrainz.org/ or last.fm are better if you actually want to track these things. - Source: Hacker News / 8 months ago
  • 2002: Last.fm and Audioscrobbler Herald the Social Web
    Https://listenbrainz.org/ is an open source scrobbler, with the advantage that it leverages the musicbrainz database and connects listens to artist and track IDs instead of names, avoiding duplicate confusion. You can keep last.fm and submit to both of you like. - Source: Hacker News / 9 months ago
  • Goodbye, Slopify
    For people moving off Spotify, have a look at https://listenbrainz.org. You can sync your listens to there and it will give you weekly recommendations. From my experience so far they are decent. Note they don't host songs themselves, but will auto-search youtube/bandcamp/etc. And play the closest match. So YMMV. - Source: Hacker News / over 1 year ago
  • The Open Music Encyclopedia
    It really is an incredible resource, and Picard is a wonderful app. Very satisfying getting a library properly tagged! Takes a while, but totally worth it. Shoutout to ListenBrainz as well, their scrobbling service: https://listenbrainz.org/. - Source: Hacker News / almost 2 years ago
  • Analyzing Spotify Stream History
    There's also ListenBrainz, run by the MusicBrainz org, which offers similar functionality without API restrictions or other paid features that Last.FM tries to push. https://listenbrainz.org/ If you wish to use your scrobble data at all programmatically this is a far better tool to use. - Source: Hacker News / over 2 years ago
View more

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
View more

What are some alternatives?

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

Last.fm - The world's largest online music service. Listen online, find out more about your favourite artists, and get music recommendations, only at Last.fm

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.

MusicBrainz - A community-maintained open source database and encyclopedia of music information.

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

stats.fm - With the click of a button you'll be logged with your Spotify account and you'll instantly gain access to a valhalla of cool stats and insights.

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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