Documentation
Analysis Tool Box Reference
150+ functions across 15 modules. Each function includes parameter documentation, code examples, and teaching notes.
Quick start
pip install analysistoolboxfrom analysistoolbox.data_processing import CreateDataOverview
import pandas as pd
df = pd.read_csv('your_data.csv')
CreateDataOverview(dataframe=df)Modules
Calculus
Mathematical functions, derivatives, limits, and optimization.
Data Collection
Gather data from web, PDFs, and external APIs.
Data Processing
Clean, transform, and prepare data for analysis.
Descriptive Analytics
Clustering, dimensionality reduction, and pattern discovery.
File Management
Batch file operations and document management.
Geospatial Analysis
Geographic data analysis, shapefiles, and mapping.
Hypothesis Testing
Rigorous statistical tests and regression analysis.
Linear Algebra
Matrix operations, transformations, and equation systems.
LLM Integration
Connect to Claude and ChatGPT APIs for AI-powered analysis.
Predictive Analytics
Machine learning models and time series forecasting.
Prescriptive Analytics
Linear optimization and recommendation systems.
Probability
Risk assessment and Bayesian belief updating.
Simulations
Monte Carlo simulations and probabilistic modeling.
Statistics
Confidence intervals and statistical inference.
Visualizations
Publication-ready charts and data visualizations.