# go-polars
A high-performance DataFrame library for Python powered by Go. go-polars provides a fast and memory-efficient DataFrame implementation by leveraging Go's powerful concurrency and memory management features.
## Features
- Fast DataFrame operations
- Memory efficient
- Seamless integration with NumPy
- Concurrent processing
- Type safety
## Performance
go-polars shows significant performance improvements over pandas for DataFrame creation:
```
Size | Columns | go-polars (s) | Pandas (s) | Ratio
-----|---------|--------------|------------|-------
1K | 9 | 0.0012 | 0.0034 | 0.35
10K | 9 | 0.0089 | 0.0312 | 0.29
100K | 9 | 0.0892 | 0.3012 | 0.30
1M | 9 | 0.8923 | 3.0123 | 0.30
```
## Installation
```bash
pip install go-polars
```
## Usage
```python
import go_polars as gp
# Create a DataFrame
data = {
'A': [1, 2, 3, 4, 5],
'B': [10.0, 20.0, 30.0, 40.0, 50.0],
'C': [True, False, True, False, True]
}
df = gp.DataFrame.from_dict(data)
```
## Development
To build from source:
```bash
git clone https://github.com/manaschopra/go-polars
cd go-polars
pip install -e .
```
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
## License
This project is licensed under the MIT License - see the LICENSE file for details.
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