research-data-auto-analysis-plotting

name	research-data-auto-analysis-plotting
description	Automatically analyze research datasets and generate publication-ready statistical tables, correlation figures, grouped comparison plots, and regression diagnostics. Use when the user wants科研数据自动分析、学术绘图、实证数据可视化、可发表级图表输出, or needs a CSV/Excel dataset turned into summary statistics and clean PNG figures.

Research Data Auto Analysis Plotting

Use this skill from F:\Python\课程\OpenClaw\cnki\skills\research-data-auto-analysis-plotting.

Workflow

1. Install dependencies:

python -m pip install -r scripts/requirements.txt

2. Run the analysis script on a CSV or Excel dataset:

python scripts/analyze_research_data.py assets/sample_research_dataset.csv --group-col treatment_group --target-col response_score --output-dir reports/research-analysis-demo

3. Read the generated outputs:

• summary_statistics.csv
• missingness.csv
• analysis_report.md
• figures/*.png

Behavior

• The script automatically reads csv/xlsx/xls.
• It computes summary statistics and missingness rates for numeric variables.
• It generates up to four distribution plots for the first numeric indicators.
• It creates a correlation heatmap when at least two numeric columns exist.
• It creates a grouped boxplot when --group-col is provided.
• It fits a simple linear regression and exports coefficients when --target-col is provided.

Parameters

Run without grouped or regression analysis:

python scripts/analyze_research_data.py path\to\data.xlsx --output-dir reports\my-study

Add grouped comparison plots:

python scripts/analyze_research_data.py path\to\data.csv --group-col industry

Add regression diagnostics:

python scripts/analyze_research_data.py path\to\data.csv --target-col roa