Software Alternatives & Startups

SwipedOn VS Matplotlib

Compare SwipedOn VS Matplotlib and see what are their differences

SwipedOn

SwipedOn is a smart but simple visitor management solution. Our paperless gateway makes connecting people intuitive and easy.

Rating
0 reviews
Pricing
Paid Free trial $19 / Monthly (Contactless sign in, Contact tracing, Visitor screening, Alerts)
Matplotlib

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

Rating
0 reviews
Pricing
Open source
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
0 vs 114
Visitor Management System popularity
100% vs 0%
alternatives listed
132 vs 240+

Base details

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

SwipedOn
Matplotlib
Website swipedon.com matplotlib.org
Pricing
Paid Free trial $19 / Monthly (Contactless sign in, Contact tracing, Visitor screening, Alerts) Official pricing
Open source
Platforms
iOS Browser iPhone Android +1
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Listed in

About SwipedOn and Matplotlib

In their own words, as submitted to SaaSHub.

SwipedOn
Matplotlib

Protect your employees and workplace from the risk of unknown exposure to viral infections such as COVID-19 Coronavirus, with contactless sign in, visitor screening and instant alert notifications. Let SwipedOn take care of all your reception desk processes - visitor management, receiving...

Read more about SwipedOn

No description of Matplotlib yet.

Features and specs

What each product offers, as listed by its team.

SwipedOn 5 features
Matplotlib 6 features
  • Contactless sign in
    Touch free check in for visitors and employees
  • Contact tracing
    Ability to run contact tracing reports
  • Visitor screening
    Screen your visitors before the enter your workplace
  • Employee wellness checks
    Check the health of your employees as they sign in
  • Proximity sign in
    Verified location sign in for employees on site
  • 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.

Analysis

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

SwipedOn
Matplotlib

Overall verdict

  • SwipedOn is a solid choice for businesses looking for a reliable and efficient visitor management system. It effectively combines functionality with ease of use, making it a worthwhile investment for companies of varying sizes.

Why this product is good

  • SwipedOn is well-regarded for its user-friendly interface and efficient visitor management solutions. It offers features like seamless sign-in processes, detailed visitor logs, customizable branding, and robust security measures. Businesses appreciate its ability to streamline front desk operations and enhance security by providing digital visitor sign-ins and badges. Additionally, SwipedOn's customer support is often praised for being responsive and helpful.

Recommended for

    SwipedOn is recommended for small to medium-sized businesses, corporate offices, schools, and any organizations needing to manage and track visitor information efficiently. It's particularly beneficial for companies prioritizing security and data management at their reception.

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.

Videos

Walkthroughs and reviews on video.

SwipedOn 3 videos + Add
Matplotlib 1 video + Add

SwipedOn Visitor Management

More videos

  • - SwipedOn Deliveries - Manage deliveries to your workplace
  • - Contact Tracing Made Easy with SwipedOn

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

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
SwipedOn
Matplotlib
100% 100%
0% 0%
100% 100%
0% 0%
0% 0%
100% 100%

User comments

Share your experience with using SwipedOn and Matplotlib. 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.

SwipedOn no reviews yet
Matplotlib no reviews yet

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Social recommendations and mentions

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

SwipedOn 0 mentions
Matplotlib 114 mentions

Tracking SwipedOn since Mar 2021.

  • 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 / 7 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 / 10 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 / 10 months ago

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Alternatives to SwipedOn and Matplotlib

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