sweetviz

name	sweetviz
version	1.0.0
description	Automated EDA comparison reports with target analysis, feature comparison, and HTML report generation for pandas DataFrames
author	workspace-hub
category	data-analysis
type	skill
capabilities	["One-line automated EDA reports","Target variable analysis","Feature comparison between datasets","Train vs test data comparison","Intra-set comparisons (subpopulations)","HTML report generation","Correlation analysis","Missing value visualization","Distribution analysis","Categorical and numerical analysis"]
tools	["sweetviz","pandas","numpy","matplotlib"]
tags	["sweetviz","eda","data-analysis","comparison","target-analysis","html-report","feature-comparison","visualization","profiling"]
platforms	["python"]
related_skills	["ydata-profiling","autoviz","pandas-data-processing","polars","great-tables"]
requires	[]
scripts_exempt	true

Sweetviz

When to Use This Skill

USE Sweetviz when:

• Dataset comparison - Comparing train vs test, before vs after, or any two datasets
• Target variable analysis - Understanding how features relate to a target
• Quick EDA reports - Need comprehensive EDA in one line of code
• Feature comparison - Analyzing feature distributions across subsets
• HTML reports - Creating shareable, interactive analysis reports
• Intra-set analysis - Comparing subpopulations within a dataset
• Data validation - Checking for data drift between datasets
• Feature selection - Identifying important features for modeling

DON'T USE Sweetviz when:

• Very large datasets - Over 1M rows (use sampling)
• Streaming data - Need real-time analysis
• Deep statistical tests - Need p-values and hypothesis testing
• Custom visualizations - Specific chart requirements
• Interactive dashboards - Use Streamlit or Dash instead
• Text/NLP analysis - Use dedicated NLP tools

Prerequisites

# Basic installation
pip install sweetviz

# Using uv (recommended)
uv pip install sweetviz pandas numpy

# With Jupyter support
pip install sweetviz pandas numpy jupyter

# Verify installation
python -c "import sweetviz as sv; print(f'Sweetviz version: {sv.__version__}')"

System Requirements

• Python 3.6 or higher
• pandas 0.25.3 or higher
• numpy
• matplotlib (for internal plotting)
• Modern web browser (for viewing HTML reports)

Complete Examples

Example 1: ML Dataset Profiling Pipeline

#!/usr/bin/env python3
"""ml_profiling_pipeline.py - Complete ML dataset profiling with Sweetviz"""

import sweetviz as sv
import pandas as pd
 numpy  np
 sklearn.model_selection  train_test_split
 datetime  datetime
 os

*See sub-skills  full details.*


```python



 sweetviz  sv
 pandas  pd
 numpy  np
 datetime  datetime
 os
 json

*See sub-skills  full details.*


```python



 sweetviz  sv
 pandas  pd
 numpy  np
 sklearn.model_selection  train_test_split
 os


*See sub-skills  full details.*



- **** (-01-): Initial release
  - Basic EDA report generation (analyze)
  - Target variable analysis
  - Dataset comparison (compare)
  - Intra- comparison (compare_intra)
  - Feature configuration options
  - Pairwise analysis control
  - ML profiling pipeline example
  - Data quality assessment example
  - Feature selection analysis example
  - Streamlit integration
  - Data pipeline integration
  - Best practices  troubleshooting



- **Official Documentation**: https://github.com/fbdesignpro/sweetviz
- **PyPI**: https://pypi.org/project/sweetviz/
- **Medium Article**: https://towardsdatascience.com/powerful-eda-exploratory-data-analysis--just-two-lines-of-code-using-sweetviz-6c943d32f34

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**Generate powerful EDA comparison reports  Sweetviz - analyze, compare,  understand your data!**



- [ Basic EDA Report (Analyze)](-basic-eda-report-analyze/SKILL.md)
- [ Target Variable Analysis](-target-variable-analysis/SKILL.md)
- [ Dataset Comparison (Compare)](-dataset-comparison-compare/SKILL.md)
- [ Intra- Comparison (Compare_Intra) (+)](-intra--comparison-compareintra/SKILL.md)
- [ Pairwise Analysis Control](-pairwise-analysis-control/SKILL.md)
- [Sweetviz  Streamlit (+)](sweetviz--streamlit/SKILL.md)
- [Sweetviz  Data Pipeline](sweetviz--data-pipeline/SKILL.md)
- [ Use Target Analysis  ML Projects (+)](-use-target-analysis--ml-projects/SKILL.md)
- [Common Issues](common-issues/SKILL.md)