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Ping Identity VS Matplotlib

Compare Ping Identity 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

Ping Identity logo Ping Identity

Ping Identity provides cloud-based, single sign-on and identity management solutions with their SAML SSO.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • Ping Identity Landing page
    Landing page //
    2023-05-10
  • Matplotlib Landing page
    Landing page //
    2023-06-14

Ping Identity features and specs

  • Comprehensive Identity Management
    Ping Identity provides a wide range of identity management solutions, including single sign-on (SSO), multi-factor authentication (MFA), and API security, making it a complete package for enterprise identity management.
  • Scalability
    It is designed to scale efficiently with the growth of an organization, suitable for both small businesses and large enterprises.
  • Strong Security Features
    Ping Identity includes robust security features such as risk-based authentication, adaptive authentication, and threat detection capabilities.
  • User Experience
    The platform focuses on delivering seamless user experiences with features like password-less authentication and frictionless SSO across multiple applications.
  • Integration Capabilities
    It offers extensive integration capabilities with a wide range of applications, both on-premises and cloud-based, including popular SaaS providers.

Possible disadvantages of Ping Identity

  • Complexity
    Given the comprehensive nature of its features, Ping Identity can be complex to implement and may require specialized knowledge and expertise.
  • Cost
    The extensive range of features and scalability come at a cost, which might be prohibitive for smaller businesses with limited budgets.
  • Learning Curve
    Due to its sophisticated features, there is a steep learning curve for administrators and users who are new to the platform.
  • Customization
    While highly capable, customization for specific needs might require significant effort and sometimes additional support from Ping Identity.
  • Support Dependency
    Organizations may find themselves reliant on Ping Identity's support services for troubleshooting and maintenance, which could lead to higher ongoing costs.

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 Ping Identity

Overall verdict

  • Ping Identity is generally considered a good option for identity and access management solutions.

Why this product is good

  • Ping Identity is known for its robust security features, flexible deployment options, and comprehensive identity management capabilities. It offers a range of services including single sign-on, multi-factor authentication, and API security, which are appreciated by many enterprises. It also supports a wide variety of integrations and has a strong reputation for reliability and customer service.

Recommended for

    Ping Identity is well-suited for medium to large enterprises looking for scalable identity solutions, especially those wanting to enhance their security posture, achieve regulatory compliance, or improve the user experience with smoother access management.

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.

Ping Identity videos

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  • Review - Stocks Close Strong; Vertex, Ping Identity, ResMed Clear Buy Points

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to Ping Identity and Matplotlib)

Ping Identity

Matplotlib

Identity And Access Management
100 100%
Identity And Access Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Identity Provider
100 100%
Identity Provider
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 Ping Identity and Matplotlib

Ping Identity Reviews

The Top 10 Single Sign-On Solutions For Business
Ping Identityโ€™s SSO solution is built to scale and enables staff to access all workspace applicationsโ€”whether mobile, cloud, enterprise, or SaaSโ€”using one set of credentials, via their centralized employee dock. This federated SSO is designed to work anywhere and from any device, and includes native support for identity standards such as SAML and OpenID Connect tokens, for...
Source: expertinsights.com
Top 10 Best SAML Identity Providers List for SSO (Pros and Cons)
Ping Identity features robust security, amazing end user experience, directory integration, and so much more. It is an intelligent identity platform that offers various cloud deployment offerings such as SSO solution, IDaaS (Identity as a service), containerized software, etc.
Source: cloudinfrastructureservices.co.uk
Top 11 Identity & Access Management Tools
Ping Identity is no slouch in other areas of IAM such as SSO, Data Access Governance, and User Directories. The product is not without complaints, mainly about its high price point and API communications. That said, it seems users are satisfied with the product and would recommend it even with those shortcomings.
Source: spectralops.io
Best identity access management software 2022
Ping Identity, founded in 2002 and one of the most well-established identity management companies in the business, was designed for hybrid IT environments. It works cleanly across public, private and hybrid clouds and with on-premises networks and applications.
Source: www.zdnet.com
The 6 Best Identity Access Management Tools
With Ping Identity we have another market leader in the IAM domain. Its solution is an ideal choice for organizations looking to enhance the security of their cloud-based assets without compromising on its customersโ€™ UI.
Source: www.comparitech.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 more popular. It has been mentiond 114 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.

Ping Identity mentions (0)

We have not tracked any mentions of Ping Identity yet. Tracking of Ping Identity recommendations started around Mar 2021.

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 / 4 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 / 7 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 / 7 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 / 8 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
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What are some alternatives?

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

OneLogin - On-demand SSO, directory integration, user provisioning and more

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

Okta - Enterprise-grade identity management for all your apps, users & devices

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

Auth0 - Auth0 is a program for people to get authentication and authorization services for their own business use.

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

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