This updated overview describes modern plotting options - commercial desktop programs like Origin, Prism, and SigmaPlot; open-source scriptable libraries in Python and R; and BI tools. It preserves the original article's intent of listing plotting software, adds guidance on choosing tools, and flags several legacy programs from early-2000s references for verification.

Some people still prefer a dedicated plotting application to visualize functions and experimental data. Today you can choose from actively developed commercial packages, lightweight desktop tools, and powerful open-source libraries that integrate into analysis workflows.

Why use plotting software

Plotting tools turn numbers into readable charts quickly. They range from GUI-driven programs for interactive tweaking to scriptable libraries for reproducible figures. Choose based on your need for statistical analysis, publication-quality graphics, automation, or ease of use.

Current mainstream options

  • Origin (OriginLab): A long-standing commercial package focused on scientific graphs, curve fitting, and instrument control. It remains a common choice in labs and engineering workflows.
  • GraphPad Prism: Popular in life sciences for statistics and common experimental plots. It targets users who want combined analysis and graphing without coding.
  • SigmaPlot: A Windows desktop application aimed at scientific graphing and data analysis; it continues to be used where step-by-step GUI workflows matter.
  • Python plotting libraries (Matplotlib, Seaborn, Plotly): Open-source, scriptable, and widely used. They scale from quick exploratory charts to complex, publication-ready figures and integrate with data pipelines.
  • R and ggplot2: A standard for statistical graphics and reproducible analysis in research and data science.
  • Spreadsheet and BI tools: Excel and Google Sheets provide basic charts; Tableau and Power BI provide interactive dashboards for exploration and presentation.

Legacy and specialized packages (status varies)

The early 2000s offered many purpose-built programs. Some remain available or have evolved; others have been discontinued. Examples you may encounter in older guides include MathGV, DPlot, Axum (MathSoft), DeltaGraph, FigP (Biosoft), PSI-Plot, SigmaPlot (earlier Jandel), and SlideWrite Plus.

If you find references to these tools in older documents, check current availability and platform support before investing time or license fees. Several entries below are historical and need verification in 2025: MathGV , DPlot 1, Axum 2, DeltaGraph 3, FigP/Biosoft 4, PSI-Plot 5, SlideWrite Plus 6.

How to choose

  • For reproducible, automated work: prefer Python or R libraries.
  • For GUI-driven, statistics-plus-graphs: try Prism, Origin, or SigmaPlot.
  • For dashboards and business visualization: consider Tableau or Power BI.
  • When working with legacy files or workflows, verify whether the original software is still supported or whether conversion/import is available.

Final note

Plotting needs and tool ecosystems have shifted toward open, scriptable libraries and cloud-enabled dashboards. Commercial desktop packages still serve users who need polished GUIs, specialized scales, or bundled analysis routines.
  1. Verify current development and download status for MathGV
  2. Verify current development and download status for DPlot
  3. Verify whether Axum (MathSoft) is still available or discontinued
  4. Verify DeltaGraph availability and vendor status
  5. Verify FigP (Biosoft) current status and platform support
  6. Verify PSI-Plot (Poly Software) current status and availability
  7. Verify SlideWrite Plus (Advanced Graphics Software) current availability

FAQs about Plotting Software

Should I pick a GUI tool or a scriptable library for plotting?
If you need reproducibility and automation, choose scriptable libraries (Python/Matplotlib, R/ggplot2). If you prefer point-and-click analysis and integrated stats, choose a GUI package like GraphPad Prism or Origin.
Can I still find the older programs mentioned in early-2000s guides?
Some legacy programs persist or were rebranded, but many were discontinued. Verify current availability and platform support before relying on them. Several specific legacy items are marked for verification in this article.
Are spreadsheets adequate for scientific plots?
For simple charts and quick exploration, spreadsheets (Excel, Google Sheets) work fine. For publication-quality figures or advanced stats, use specialized plotting libraries or scientific graphing software.
Which tools are best for interactive dashboards?
Tableau and Power BI are leading choices for interactive dashboards. Plotly and Dash (Python) also enable web-deployable interactive visualizations.

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