Metadata-Version: 2.4
Name: bizlens
Version: 2.3.2
Summary: BizLens: Complete analytics platform with 13 interactive Jupyter notebooks covering descriptive analytics, statistical inference, regression, machine learning, clustering, process mining, and time series analysis. Built-in Rich tables, dual Pandas/Polars support, and production-ready code examples.
Home-page: https://github.com/solutiongate-learn/bizlens
Author: Sudhanshu Singh
Author-email: Sudhanshu Singh <cc9n8y8tqc@privaterelay.appleid.com>
License: MIT
Project-URL: Homepage, https://github.com/solutiongate-learn/bizlens
Project-URL: Documentation, https://github.com/solutiongate-learn/bizlens#readme
Project-URL: Repository, https://github.com/solutiongate-learn/bizlens
Project-URL: Bug Tracker, https://github.com/solutiongate-learn/bizlens/issues
Project-URL: PyPI, https://pypi.org/project/bizlens/
Keywords: analytics,statistics,education,business-intelligence,descriptive-analytics,eda,data-visualization,outlier-detection,normality-test,synthetic-data,process-mining,teaching,sample-vs-population,skewness,data-science
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Education
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Operating System :: OS Independent
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.21.0
Requires-Dist: pandas>=1.5.0
Requires-Dist: scipy>=1.9.0
Requires-Dist: statsmodels>=0.14.2
Requires-Dist: matplotlib>=3.6.0
Requires-Dist: seaborn>=0.12.0
Requires-Dist: plotly>=5.0.0
Requires-Dist: networkx>=2.6.0
Requires-Dist: scikit-learn>=1.0.0
Requires-Dist: rich>=13.0.0
Provides-Extra: jupyter
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Requires-Dist: ipython>=7.30.0; extra == "jupyter"
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Provides-Extra: process-mining
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Dynamic: author
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# BizLens 📊

**Business analytics, statistical inference, process mining, and machine learning — all in one package**

BizLens is a comprehensive Python library designed for business analysts, data scientists, educators, and students. It combines professional statistical analysis, beautiful Rich tables, interactive visualizations, and built-in business process mining capabilities — all accessible with a simple `pip install`.

---

## 🚀 Open in Google Colab — No Installation Needed

Click any link below to launch a notebook instantly in your browser:

### Core Analytics

| Notebook | Colab Link | What You'll Learn |
|----------|-----------|-------------------|
| **Quick Start** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Quick_Start_bizlens.ipynb) | Overview, frequency tables, outlier detection |
| **Descriptive Analytics** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Descriptive_Analytics.ipynb) | Frequency, percentile, contingency, data profile |
| **Statistical Inference** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Statistica_Inference.ipynb) | Confidence intervals, t-tests, ANOVA, correlation |
| **Chi-Square & Association** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_ChiSquareTest.ipynb) | Chi-square, contingency tables, Cramér's V |
| **Probability & Distributions** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Probability_Distribution_Simulation.ipynb) | Distribution fitting, simulation, sampling |

### Machine Learning

| Notebook | Colab Link | What You'll Learn |
|----------|-----------|-------------------|
| **Linear & Multiple Regression** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Linear_Multiple_Linear_Regression.ipynb) | OLS regression, diagnostics, predictions |
| **Logistic Regression** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Logistics_Regression.ipynb) | Binary classification, ROC, confusion matrix |
| **Decision Trees & Random Forests** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Decision_Trees_Random_Forests.ipynb) | Tree models, feature importance, ensembles |
| **PCA & Clustering** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_PCA_Clustering.ipynb) | Dimensionality reduction, K-Means, DBSCAN |
| **Conjoint Analysis** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Conjoint_Analysis.ipynb) | Preference modeling, attribute utilities |
| **Q-Learning** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Q_Learning.ipynb) | Reinforcement learning basics, Q-table |

### Advanced Analytics & Process Mining

| Notebook | Colab Link | What You'll Learn |
|----------|-----------|-------------------|
| **Master Process Mining** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Master_Process_Mining.ipynb) | Case metrics, bottlenecks, variants, resources, workflow analysis |
| **Time Series & Anomaly Detection** | [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/solutiongate-learn/bizlens/blob/main/notebooks/New_Time_Series_Anomaly.ipynb) | Temporal patterns, trend analysis, anomaly detection |

> All notebooks automatically install BizLens on first run — just click the Colab badge and run the first cell.

---

## 💾 Installation

```bash
pip install bizlens
