RAWGraphs

Website

rawgraphs.io

Categories

#Charting Libraries #Data Dashboard #Data Visualization #Javascript UI Libraries

Bokeh

Website

docs.bokeh.org

Categories

#Charting Libraries #Data Visualization #Data Dashboard #Javascript UI Libraries

RAWGraphs features and specs

• User-Friendly Interface
  RAWGraphs provides an intuitive drag and drop interface, making it accessible for users with various technical skills.
• Open Source
  Being open source, RAWGraphs allows for customization and community contributions, promoting transparency and flexibility.
• Supports Multiple Data Formats
  RAWGraphs supports a variety of input formats like CSV, TSV, JSON, etc., enhancing its adaptability to different data sources.
• Extensive Visualization Types
  Offers a wide range of visualization types such as bar graphs, scatter plots, and network graphs, catering to diverse analytical needs.
• No Installation Required
  As a web-based tool, it does not require any installation, making it easy to access and use anywhere with an internet connection.
• Export Options
  Allows exporting visualizations in vector (SVG) and raster (PNG) formats, which is valuable for high-quality reporting and presentations.

Possible disadvantages of RAWGraphs

• Limited Interactivity
  Visualizations created with RAWGraphs are generally static, lacking advanced interactive features found in other tools.
• Performance with Large Datasets
  May struggle with performance issues when handling very large datasets, which can limit its use for extensive data analytics.
• Learning Curve for Advanced Features
  While basic functionalities are user-friendly, leveraging advanced features and customizations may require a steeper learning curve.
• Dependency on Internet
  As a web-based application, it requires an internet connection to function, which can be a limitation in restricted or offline environments.
• Limited Data Manipulation
  Provides basic data manipulation features, but lacks the depth and complexity available in specialized data processing tools.
• Support and Documentation
  As an open-source project, it may not have the extensive support and documentation available with commercial visualization tools.

Bokeh features and specs

• Interactive Visualizations
  Bokeh is designed specifically for creating interactive and highly customizable visualizations, making it suitable for engaging data exploration.
• Python Integration
  Bokeh integrates well with the Python ecosystem, allowing direct use of pandas, NumPy, and other Python libraries, facilitating seamless data manipulation and visualization.
• Web Compatibility
  Bokeh generates plots that are ready to be embedded into web applications, making it a powerful tool for creating dashboards and interactive reports.
• Server Functionality
  Bokeh provides a server component that allows users to build and deploy sophisticated interactive applications using just Python.
• Variety of Plotting Options
  Bokeh offers a wide range of plotting capabilities including charts, maps, and streamgraphs, enabling users to create complex visual stories.

Possible disadvantages of Bokeh

• Learning Curve
  Bokeh may have a steeper learning curve for users unfamiliar with JavaScript or those looking for a very simple or quick plotting tool.
• Performance Issues
  When dealing with very large datasets, Bokeh might suffer from performance issues, as it is primarily client-side rendering.
• Limited 3D Capabilities
  Bokeh's support for 3D plotting is limited compared to other visualization libraries like Plotly, potentially restricting its use for applications that require 3D visualizations.
• Documentation and Community Size
  While Bokeh has good documentation, its user community is smaller compared to more mature libraries like Matplotlib, which can mean fewer resources and third-party support options.

RawGraphs Walkthrough

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