crosstabs-analytics 1.0.0

AI-powered statistical analysis for Jupyter notebooks

Crosstabs Analytics

AI-powered statistical analysis for Jupyter notebooks.

Installation

pip install crosstabs-analytics

Quick Start

import pandas as pd
from crosstabs_analytics import CrosstabsAnalyzer

# Load your data
df = pd.read_csv('your_data.csv')

# Initialize analyzer
crosstabs = CrosstabsAnalyzer()

# Analyze your data
results = crosstabs.analyze(df)
display(results)

Features

• AI-Powered Analysis: Get GPT-4 powered statistical insights
• Beautiful Results: View results in interactive HTML format
• Multiple Export Formats: PDF, Excel, JSON
• Batch Processing: Analyze multiple datasets
• Custom Parameters: Tailor analysis to your needs
• Integration: Works with matplotlib, seaborn, and other tools

Usage Examples

Basic Analysis

from crosstabs_analytics import CrosstabsAnalyzer

crosstabs = CrosstabsAnalyzer()
results = crosstabs.analyze(df)
display(results)

Batch Analysis

datasets = {
    'Q1_2024': df1,
    'Q2_2024': df2,
    'Q3_2024': df3
}

batch_results = crosstabs.batch_analyze(datasets)

Export Results

raw_results = crosstabs.get_raw_results(df)
pdf_url = crosstabs.export_pdf(raw_results['analysis_id'])
excel_url = crosstabs.export_excel(raw_results['analysis_id'])

Requirements

• Python 3.8+
• pandas
• numpy
• requests
• matplotlib
• seaborn
• jupyter

Support

• Website: https://crosstabs.com
• Documentation: https://docs.crosstabs.com
• Support: [e-mail]
• GitHub: https://github.com/crosstabs/crosstabs-analytics

License

MIT License