ZingChart

Website

zingchart.com

Pricing URL

Official ZingChart Pricing

$ Details

freemium $99.0 / Annually (Website license for a single website or domain)

Platforms

Browser Windows iOS Android Mac OSX Linux Web Cross Platform JavaScript PHP Google Chrome Firefox Java iPhone Safari TypeScript

Release Date

2009 January

Categories

#Charting Libraries #Charts #Charting Tools And Libraries #Data Visualization #Data Dashboard #Org Charts #Business Intelligence

Matplotlib

Website

matplotlib.org

Pricing URL

-

$ Details

Platforms

-

Release Date

-

Categories

#Data Visualization #Technical Computing #Data Science And Machine Learning #Application And Data

ZingChart features and specs

• Feature-Rich
  ZingChart offers a wide range of chart types and customization options, enabling developers to create detailed and highly interactive visualizations.
• Performance
  Designed for high performance, ZingChart can handle large data sets efficiently, making it suitable for applications that require processing extensive information.
• Cross-Platform Support
  The library supports multiple platforms, ensuring that charts render correctly across various devices and web browsers.
• Ease of Use
  With extensive documentation and examples, as well as an intuitive API, ZingChart is accessible for developers at different skill levels.
• Interactivity
  ZingChart provides numerous interactive features, such as tooltips, animations, and events, which enhance user engagement.
• Community and Support
  There is a strong community and professional support available, offering assistance and resources for troubleshooting and improving your projects.

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 ZingChart

Analysis of Matplotlib

ZingChart Flash vs HTML5 Speed Test on Nexus One with Froyo

More videos:

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial