DataThief III VS QtiPlot

• Ease of Use
  DataThief III provides a straightforward interface that makes it easy for users to extract data from graphs, even if they have limited technical skills.
• Support for Various Graphs
  The software can handle a variety of graphs such as line graphs, scatter plots, and bar charts, making it versatile for different data extraction needs.
• Interactive Features
  DataThief III offers interactive features that allow users to manually adjust data points, ensuring precise data extraction.
• Cross-Platform Compatibility
  Available for multiple operating systems, including Windows, macOS, and Linux, which allows for broader accessibility.

Possible disadvantages

• Limited Output Formats
  The software primarily supports output to CSV format, which might require additional work for users who need other formats.
• No Advanced Analysis Tools
  DataThief III focuses solely on data extraction and does not provide advanced analysis tools, requiring users to use additional software for analysis.
• Manual Data Adjustment
  While manual adjustment contributes to accuracy, it can be time-consuming if many data points require it.
• Older User Interface
  The interface might feel outdated compared to more modern software solutions which can affect user experience.

• Open Source
  QtiPlot is an open-source software, which allows users to inspect the source code and contribute to its development. This fosters community-driven improvements and ensures transparency.
• Cross-Platform Support
  QtiPlot is available for multiple platforms including Windows, macOS, and Linux, providing flexibility for users who work across different operating systems.
• Scientific Data Visualization
  QtiPlot offers a range of data visualization tools specifically designed for scientific research, making it easy to create publication-quality graphs and plots.
• Cost-Effective
  Being available as free software, QtiPlot is a cost-effective alternative to commercial data analysis and visualization tools, making it accessible for students and researchers with limited budgets.
• Custom Scripting
  QtiPlot supports Python scripting, allowing users to automate tasks and extend functionality through custom scripts, which enhances its versatility.

Possible disadvantages

• Steep Learning Curve
  New users might find QtiPlot challenging to learn, especially if they do not have a background in data analysis or visualization tools, due to its complex interface and feature set.
• Limited Documentation
  The documentation for QtiPlot may be less comprehensive compared to some proprietary software, potentially making it difficult for users to find solutions to specific problems.
• Performance Issues
  For very large datasets, QtiPlot may experience performance issues, including slow processing speeds or application crashes, limiting its usability for extensive data analysis.
• Lack of Advanced Features
  Compared to some commercial alternatives, QtiPlot may lack certain advanced features and tools for specialized scientific analysis, which can be a limitation for expert users.
• Community Support
  While there is a community of open-source users, the support might not be as immediate or structured as commercial customer support, which can delay problem resolution.

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QtiPlot Intro #3: scatter plot, linear regression, error bars & reading data from graphs

More videos

• Show HN: Extract Data from Line Chart Image

  Glad to see some work in this space. While I was doing my PhD all I had was https://datathief.org/, which usually did the job, but had some limitations and was Java-based. - Source: Hacker News / over 2 years ago

• Ask HN: How can I convert any chart image into raw data automatically?

  I don’t know if this is still up-to-date, but a decade ago I used to use this tool in cases where I couldn’t access numbers behind published graphs: https://datathief.org/. - Source: Hacker News / almost 4 years ago

• [OC] Very High Correlation Between Campaign Spending and Election Results in the United States

  Use https://datathief.org/ to convert this chart to a data table if you want to try it. Source: about 4 years ago

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Tracking QtiPlot since Mar 2021.