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Frill VS Matplotlib

Compare Frill VS Matplotlib and see what are their differences

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

Frill logo Frill

A better way to collect customer feedback

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Frill Landing page
    Landing page //
    2023-08-20
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Frill features and specs

  • User-friendly Interface
    Frill offers an intuitive and easy-to-navigate user interface, making it accessible for users of all experience levels.
  • Customizable Boards
    Users can customize their feedback boards to align with their brand's aesthetics and requirements, providing a more personalized experience.
  • Feature Prioritization
    Frill enables teams to prioritize suggestions and feedback, helping to focus on the most impactful changes and enhancements.
  • Integration with Popular Tools
    Frill integrates seamlessly with other popular tools and platforms, such as Slack, Zapier, and Intercom, promoting better workflow efficiency.
  • Public and Private Boards
    Frill allows for the creation of both public and private boards, giving flexibility in sharing feedback and ideas internally or with customers.

Possible disadvantages of Frill

  • Cost
    Frill offers various pricing plans, which might be expensive for small businesses or startups with limited budgets.
  • Limited Advanced Features
    While Frill is user-friendly, it may lack some advanced features required by larger enterprises with more complex feedback management needs.
  • Dependency on Integrations
    For full functionality, users may rely heavily on integrations with other tools, which can be a limitation if those tools are not already in use.
  • Learning Curve for Customization
    Despite its user-friendly nature, there might be a slight learning curve for users to fully customize their boards and utilize all features effectively.
  • Limited Analytics
    The platform might offer limited in-depth analytics compared to specialized feedback analysis tools, which can be a drawback for data-driven decision-making.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of Frill

Overall verdict

  • Overall, Frill.co is a good choice for businesses looking for a streamlined way to handle product feedback and manage their development process. Its intuitive interface and comprehensive features make it a valuable tool for both small and medium-sized businesses aiming to improve their product offerings based on customer insights.

Why this product is good

  • Frill.co is a product feedback and roadmap tool designed to help companies gather and manage customer feedback more effectively. It provides features like idea boards, where users can submit and vote on ideas, roadmaps to keep track of development progress, and changelogs to announce updates. These tools can enhance customer engagement and ensure product development aligns with user needs.

Recommended for

    Frill.co is particularly recommended for product managers, SaaS companies, and startups looking to prioritize and manage user feedback effectively. It is also beneficial for teams looking to enhance customer interaction and transparency by clearly communicating product development progress and updates.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

Frill videos

+ Add

Frill review | Collect Your Customer Feedback

More videos:

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  • Review - Bass Fishing Review Chasebaits Frill Seeker Wakebait

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Frill and Matplotlib)

Frill

Matplotlib

Customer Feedback
100 100%
Customer Feedback
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
User Feedback
100 100%
User Feedback
0% 0
Technical Computing
0 0%
Technical Computing
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 Frill and Matplotlib

Frill Reviews

  1. Denis Anisimov
    ยท CTO at Introwise ยท
    Easy to embed and customize

    We are using Frill to collect user feedback and feature requests, as well as post announcements about new feature updates to our users.

    I love how easy it was to connect Frill with our own system, including SSO support for seamless users authentication. We also integrated the Frill widget right into our product user's dashboard so it's easy to distribute announcements and collect new feature ideas this way.

    One of the most satisfying product experiences I've had with a tool for our business. Their customer support is top-notch as well.

    ๐Ÿ Competitors: Nolt.io, Upvoty
    ๐Ÿ‘ Pros:    Inexpensive|Customizable|Fast|Great customer support|Well designed
  2. Sam Hulick
    ยท CEO at ReelCrafter ยท
    Best one!

    Frill is thoughtfully designed and simple to use while offering a complex and powerful level of customizability. It integrates seamlessly into our web app and has become a crucial part of the feedback loop with our customers

    ๐Ÿ Competitors: Canny.io
10 Best Canny Alternatives and Competitors in 2025
Frill is a customer feedback management tool you can use as a web app or widget. Use the customization features to build unique boards where you brainstorm ideas and meet customer needs. ๐Ÿง 
Source: clickup.com
Top 10 FeatureBase alternatives you should evaluate in 2024
With its simple design and easier supports, Frill (opens in new tab) can be one of the best alternatives for Featurebase. Frill has an updated and modern UI and it is simple to use. Also Frill is a language friendly software which can translate into any language. Though it has several attracting features, Frillโ€™s drawback should also be taken into consideration.
Source: featureos.app
17 Best Canny Alternatives in 2024
Frill helps companies engage with their customers, gather feedback and prioritize feature requests. It also allows companies to create online communities where users can discuss products and services with each other.
Source: supahub.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib seems to be a lot more popular than Frill. While we know about 114 links to Matplotlib, we've tracked only 2 mentions of Frill. 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.

Frill mentions (2)

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 5 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 8 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 8 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing Frill and Matplotlib, you can also consider the following products

Canny.io - Canny helps you collect and organize feature requests to better understand customer needs and prioritize your roadmap.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Featurebase - The all-in-one toolkit for managing your customer feedback.

NumPy - NumPy is the fundamental package for scientific computing with Python

productboard - Beautiful and powerful product management.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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