semvec/pypi-packages huggingface dataset:
explainviz 1.0.0
ExplainViz: Visualization that explains data behavior and bias
License: MIT
Requires Python: >=3.10

# ExplainViz

ExplainViz is a Python 3.10+ visualization library that not only plots data,
but also explains what is happening inside the data using clear,
rule-based statistical insights.

It is designed to sit on top of Matplotlib and provide:
- Automatic plots
- Distribution explanations
- Stability and change detection
- Relationship analysis
- Group bias and fairness checks

ExplainViz focuses on **clarity, reliability, and real-world usability** —
no black-box AI, no hidden magic.

---

## ✨ Key Features

- 📊 Automatic plot selection (numeric, grouped data)
- 📈 Distribution analysis (skewness, tails)
- ⚡ Sudden change detection in data
- 🔗 Strong relationship detection between variables
- ⚖️ Group bias and imbalance checks
- 🧠 Human-readable explanations alongside plots
- 🐍 Python 3.10+ compatible

---

## 📦 Installation

```bash
pip install explainviz
worlddatax 1.0.0
Comprehensive offline datasets for global country, currency, and geography metadata.
License: MIT
Requires Python: >=3.8
Keywords: countries, geography, iso, world, dataset

# worlddatax

worlddatax is a production-ready Python package that ships an up-to-date, structured snapshot of worldwide geographic and country metadata. It exposes a simple, beginner-friendly API that reads from packaged JSON datasets covering every UN-recognised sovereign state.

## Features

- 195 countries with ISO codes, capitals, continents, currencies, and international dialling prefixes
- Deep-dives for key markets with state, province, and city coverage
- Clean Python functions that never print or raise on missing records—receiving `None` or empty collections instead
- Zero runtime network access; all data is bundled in JSON and loaded on demand with caching

## Installation

Install the library directly from a source checkout or from PyPI (when published):

```bash
pip install worlddatax
```

For local development use:

```bash
pip install -e .
```

## Quick start

```python
from worlddatax import (
		get_all_countries,
		get_country_by_iso,
		get_countries_by_continent,
		get_states,
		get_cities,
		get_currency,
		get_phone_code,
)

india = get_country_by_iso("IND")
asia = get_countries_by_continent("Asia")
states = get_states("United States")
california_cities = get_cities("United States", "California")
yen = get_currency("Japan")
usa_codes = get_phone_code("United States")

print(india["capital"])          # New Delhi
print(len(asia))                  # 46
print(states[:3])                 # ['Alabama', 'Alaska', 'Arizona']
print(california_cities)          # ['Los Angeles', 'San Francisco']
print(yen)                        # {'code': 'JPY', 'name': 'Japanese yen', 'symbol': '¥'}
print(usa_codes)                  # ['+1']
```

## Packaged data

- Countries: names, ISO-2, ISO-3, capitals, continents, currency metadata, international calling prefixes
- States and provinces: complete lists for Australia, Brazil, Canada, China, France, Germany, India, and the United States
- Cities: curated coverage for major regions within the above countries
- Currencies: code, display name, and symbol for every currency referenced by the dataset
- Continents: continent-to-country mappings for simplified grouping

Datasets are fetched from the public [REST Countries](https://restcountries.com) service during packaging and bundled into JSON files inside the distribution. All files are UTF-8 encoded and ship with the wheel, ensuring offline availability.

## Project layout

```
worlddatax/
	worlddatax/           # Package modules
	data/                 # JSON datasets bundled with the wheel
	tests/                # Automated contract checks
```

## Testing

Run the included test suite with `pytest`:

```bash
pytest
```

## License

worlddatax is released under the MIT License. See [LICENSE](LICENSE) for details.