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Matplotlib VS ArtShow.app

Compare Matplotlib VS ArtShow.app and see what are their differences

Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

Rating
0 reviews
Pricing
Open source
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Alternatives Is it good?
ArtShow.app

Capture, enhance, store, organize, share & download and print your favorite art! Download the App & Get started with a Free 1 Month Trial.

Rating
0 reviews
Pricing
Paid Free trial $1.99 / Monthly (Add up to 10 pictures a month)
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Alternatives Is it good?
Grapple
Do-It-Yourself Data Analytics & Business Intelligence, Powered by AI sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, Matplotlib seems to be more popular. It has been mentioned 114 times since March 2021.

social mentions
114 vs 0
Data Science And Machine Learning popularity
100% vs 0%
alternatives listed
238 vs 6

Base details

Website, pricing, platforms and company facts side by side.

Matplotlib
ArtShow.app
Website matplotlib.org artshow.app
Pricing
Open source
Paid Free trial $1.99 / Monthly (Add up to 10 pictures a month) Official pricing
Platforms —
Android iPhone Web
Company — Startup from the United Kingdom · 1 - 9 employees · 2025
Listed in
Data Science And Machine Learning Development Data Visualization Javascript UI Libraries +1
Art Art Tools Family Organizer On Demand Printing +1

About Matplotlib and ArtShow.app

In their own words, as submitted to SaaSHub.

Matplotlib
ArtShow.app

No description of Matplotlib yet.

We wanted a simple way to digitize, preserve, and organise our family's art – to capture and show it off ‘in its best light’. There wasn’t one that really fitted the bill. So we set out to create one. ArtShow helps you to capture & transform kids’ art and your own creations into digital...

Read more about ArtShow.app

Features and specs

What each product offers, as listed by its team.

Matplotlib 6 features
ArtShow.app 6 features
  • 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

  • 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.
  • Capture
    Capture your Art with your mobile phone camera or upload a picture file
  • Enhance
    Enhance your Art with our AI driven auto-clipping and enhancement
  • Store
    Store your Art and build galleries
  • Organize
    Attribute your art to your artists and arrange your art into categories
  • Download & Share
    Download and share your art quickly and easily
  • Print
    Print your art to a wide range of print and collage products custom-printed and delivered to your door

Analysis

An editorial look at what each product does well and who it suits.

Matplotlib
ArtShow.app

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.

Overall verdict

  • ArtShow.app appears to be a niche platform for showcasing and organizing art exhibitions online, offering a reasonable option for artists and galleries seeking a digital presence, though it may lack the extensive features and market reach of larger established art platforms.

Why this product is good

  • Provides a dedicated space for artists to display their portfolios and exhibitions online
  • Likely offers a simpler, more focused interface compared to broader creative platforms
  • Can help artists and small galleries establish a web presence without building a custom site
  • May include tools tailored specifically for organizing virtual or physical art shows

Recommended for

  • Independent artists looking for a simple online portfolio solution
  • Small galleries wanting to organize and promote virtual exhibitions
  • Art students or emerging creatives needing an affordable showcase platform
  • Event organizers hosting niche or local art shows

Videos

Walkthroughs and reviews on video.

Matplotlib 1 video + Add
ArtShow.app 1 video + Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

ArtShow App Video

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Matplotlib
ArtShow.app
100% 100%
Data Science And Machine Learning
0% 0%
0% 0%
On Demand Printing
100% 100%
100% 100%
Technical Computing
0% 0%
0% 0%
Family Organizer
100% 100%

Questions & Answers

As answered by people managing Matplotlib and ArtShow.app.

What makes your product unique?

ArtShow.app's answer:

We wanted a simple way to digitize, preserve, and organize our family's art – to capture and show it off ‘in its best light’. There wasn’t one that really fitted the bill. So we set out to create one.

Why should a person choose your product over its competitors?

ArtShow.app's answer:

ArtShow utilises the latest AI-driven clipping and enhancement technology to ensure your amazing art stays amazing. Our low cost flexible monthly plans let you add to your gellery when you need to, and our custom-print shop ensures you always have great gifts for family young and old.

How would you describe the primary audience of your product?

ArtShow.app's answer:

Our primary audience would be busy parents with young kids who like nothing better than to paint, draw and create!

What's the story behind your product?

ArtShow.app's answer:

Our founder created framed collages of kids artwork for many years for a small group of friends and customers. With advancements in technology it became possible to launch the service as a mobile app - so we did!

Which are the primary technologies used for building your product?

ArtShow.app's answer:

AI, APIs, cloud servers, android, iOS, web...

Who are some of the biggest customers of your product?

ArtShow.app's answer:

Laura K probably deserves a special mention!

User comments

Share your experience with using Matplotlib and ArtShow.app. For example, how are they different and which one is better?

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Matplotlib no reviews yet
ArtShow.app no reviews yet

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We have no reviews of ArtShow.app yet. Be the first one to post

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Matplotlib 114 mentions
ArtShow.app 0 mentions
  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib — the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review.... - Source: dev.to / 8 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes it’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... - Source: dev.to / 11 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 / 11 months ago

View more

Tracking ArtShow.app since Sep 2025.

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