critiplot 1.1.0

Visualize risk-of-bias in systematic reviews and meta-analyses

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

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

• Python Package: https://pypi.org/project/critiplot/1.1.0/

---

Data & Template

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

---

📥 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-main.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.

---

⚡ Usage

Import the plotting functions from the package:

import critiplot

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

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")

Theme options:

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

---

Sample

Use Critiplot Python package validation repository if you want: https://github.com/critiplot/Critiplot-Validation

---

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.

---

Info

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

---

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: "v1.1.0"
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: "v1.1.0"
  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 (v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.17338087

---

📜 License

Apache 2.0 © 2025 Vihaan Sahu

---

Example / Result

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

NOS

GRADE

ROBIS

JBI Case Report

JBI Case Series