Pretty ASCII printing of tabular data
Project description
# tableprint
:clipboard: pretty ASCII printing of tabular data in python :snake:
![Example output](https://raw.githubusercontent.com/nirum/tableprint/master/example.png)
## About
`tableprint` lets you easily print pretty ASCII formatted tables of data.
Unlike other modules, you can print single rows of data at a time (useful for printing ongoing computation results).
Also, `tableprint` is fast (minimal processing required) and is therefore relevant for printing updates during speed-intensive computations.
## Installation
```bash
pip install tableprint
```
## Usage
The `tableprint.table()` function takes in a matrix of data, a list of headers, and an optional dictionary of parameters. To print a dataset consisting of 10 rows of 3 different columns:
```python
import tableprint
import numpy as np
data = np.random.randn(10,3)
headers = ['Column A', 'Column B', 'Column C']
tableprint.table(data, headers)
```
## Dependencies
- Python 2.7 or 3.3+
## Version
- 0.1.0 (Feb 24 2015) Initial release
## License
MIT. See `LICENSE.md`
:clipboard: pretty ASCII printing of tabular data in python :snake:
![Example output](https://raw.githubusercontent.com/nirum/tableprint/master/example.png)
## About
`tableprint` lets you easily print pretty ASCII formatted tables of data.
Unlike other modules, you can print single rows of data at a time (useful for printing ongoing computation results).
Also, `tableprint` is fast (minimal processing required) and is therefore relevant for printing updates during speed-intensive computations.
## Installation
```bash
pip install tableprint
```
## Usage
The `tableprint.table()` function takes in a matrix of data, a list of headers, and an optional dictionary of parameters. To print a dataset consisting of 10 rows of 3 different columns:
```python
import tableprint
import numpy as np
data = np.random.randn(10,3)
headers = ['Column A', 'Column B', 'Column C']
tableprint.table(data, headers)
```
## Dependencies
- Python 2.7 or 3.3+
## Version
- 0.1.0 (Feb 24 2015) Initial release
## License
MIT. See `LICENSE.md`