Critiplot is an open-source Python package for visualizing risk-of-bias (RoB) assessments across multiple evidence synthesis tools:

• Newcastle-Ottawa Scale (NOS)

• JBI Critical Appraisal Checklists (Case Report / Case Series)

• GRADE certainty of evidence

• ROBIS for systematic reviews

• MMAT (Mixed Methods Appraisal Tool)

• It produces publication-ready traffic-light plots and stacked bar charts for summarizing study quality.

• Python Package: https://pypi.org/project/critiplot/

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Data & Template

• Please strictly follow the Data & Template (available as .csv & excel format) as mentioned in the main Critiplot Web: critiplot.vercel.app

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📥 Installation

You can install Critiplot directly from PyPI (works the best with Python 3.13 version):

pip install critiplot

Or install locally from source:

# Clone repository
git clone https://github.com/aurumz-rgb/Critiplot-Package.git
cd Critiplot-Package

# Install requirements
pip install -r requirements.txt

# Install package locally
pip install .

Requires Python 3.11+ (Recommended: use Python 3.13 version), Matplotlib, Seaborn, and Pandas.

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⚡ Usage

To visualize your data, import the plotting functions from critiplot and run them directly in a Python script (.py) or in the terminal using python3.

import critiplot

from critiplot import plot_nos, plot_jbi_case_report, plot_jbi_case_series, plot_grade, plot_robis, plot_mmat

Example:

# NOS
plot_nos("tests/sample_nos.csv", "tests/output_nos.png", theme="blue")

# ROBIS
plot_robis("tests/sample_robis.csv", "tests/output_robis.png", theme="smiley")

# JBI Case Report
plot_jbi_case_report("tests/sample_jbi_case_report.csv", "tests/output_case_report.png", theme="gray")

# JBI Case Series
plot_jbi_case_series("tests/sample_jbi_case_series.csv", "tests/output_case_series.png", theme="smiley_blue")

# GRADE
plot_grade("tests/sample_grade.csv", "tests/output_grade.png", theme="green")

# MMAT
plot_mmat("tests/sample_mmat.csv", "tests/output_mmat.png", theme="default")

Theme options:

• NOS, JBI Case Report / Case Series, ROBIS, MMAT: "default", "blue", "gray", "smiley", "smiley_blue"
• GRADE: "default", "green", "blue"
• Default theme is used if omitted.

You can also use Critiplot Python package validation repository where validation was done using .py file (Was done for v2.0.0) You can check it out here: https://github.com/critiplot/Critiplot-Validation

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📂 Example Datasets

For reproducibility and reference, example .csv and .xlsx files are included in the repository:

Tool / Assessment Type	Example Files
Newcastle–Ottawa Scale (NOS)	tests/sample_nos.csv, tests/sample_nos.xlsx
ROBIS	tests/sample_robis.csv, tests/sample_robis.xlsx
GRADE	tests/sample_grade.csv, tests/sample_grade.xlsx
JBI Case Report	tests/sample_case_report.csv, tests/sample_case_report.xlsx
JBI Case Series	tests/sample_case_series.csv, tests/sample_case_series.xlsx
MMAT	tests/sample_mmat.csv, tests/sample_mmat.xlsx

You can open these files directly to view the expected column format and data layout for each plotting function.

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🧩 Reproducibility

All results in the paper can be reproduced by following the method as mentioned in Usage

I would personally recommend testing using Python 3.13

You can also use Critiplot Python package validation repository (Was done for v1.0.3, newer version visualizes an additional plot i.e. MMAT) You can check it out here: https://github.com/critiplot/Critiplot-Validation

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Notes

• Generates traffic-light plots and weighted bar charts using Matplotlib / Seaborn.
• Input data must be a CSV or Excel file following each tool’s required columns.
• Critiplot is a visualization tool only; it does not compute risk-of-bias.

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Info

• Web version also exists for this package.
• GitHub: https://github.com/aurumz-rgb/Critiplot-main
• Web: https://critiplot.vercel.app

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Citation

If you use this software, please cite it using the following metadata:

cff-version: 1.2.0
message: "If you use this software, please cite it using the following metadata."
title: "Critiplot: A Python based Package for risk-of-bias data visualization in Systematic Reviews & Meta-Analysis"
version: "v2.1.1"
doi: "10.5281/zenodo.17338087"
date-released: 2025-09-06
authors:
  - family-names: "Sahu"
    given-names: "Vihaan"
preferred-citation:
  type: software
  authors:
    - family-names: "Sahu"
      given-names: "Vihaan"
  title: "Critiplot: A Python based Package for risk-of-bias data visualization in Systematic Reviews & Meta-Analysis"
  version: "v2.1.1"
  doi: "10.5281/zenodo.17338087"
  year: 2025
  url: "https://doi.org/10.5281/zenodo.17338087"

Or cite as:

Sahu, V. (2025). Critiplot: A Python based Package for risk-of-bias data visualization in Systematic Reviews & Meta-Analysis (v2.1.1). Zenodo. https://doi.org/10.5281/zenodo.17338087

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📜 License

Apache 2.0 © 2025 Vihaan Sahu

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Example / Result

Here’s an example traffic-light plot generated using Critiplot with different themes:

NOS

GRADE

ROBIS

JBI Case Report

JBI Case Series

MMAT Descriptive Plot

MMAT Non-Randomized Plot

MMAT Mixed-Methods Plot

MMAT Randomized Plot

MMAT Qualitative Plot