Metadata-Version: 2.1
Name: treeplot
Version: 0.1.1
Summary: Python package treeplot vizualizes a tree based on a randomforest or xgboost model.
Home-page: https://github.com/erdogant/treeplot
Author: Erdogan Taskesen
Author-email: erdogant@gmail.com
License: UNKNOWN
Download-URL: https://github.com/erdogant/treeplot/archive/0.1.1.tar.gz
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3
Description-Content-Type: text/markdown
Requires-Dist: sklearn
Requires-Dist: numpy
Requires-Dist: graphviz
Requires-Dist: xgboost

# treeplot

[![Python](https://img.shields.io/pypi/pyversions/treeplot)](https://img.shields.io/pypi/pyversions/treeplot)
[![PyPI Version](https://img.shields.io/pypi/v/treeplot)](https://pypi.org/project/treeplot/)
[![License](https://img.shields.io/badge/license-MIT-green.svg)](https://github.com/erdogant/treeplot/blob/master/LICENSE)
[![Downloads](https://pepy.tech/badge/treeplot/week)](https://pepy.tech/project/treeplot/week)
[![Donate](https://img.shields.io/badge/donate-grey.svg)](https://erdogant.github.io/donate/?currency=USD&amount=5)

* treeplot is Python package

### Contents
- [Installation](#-installation)
- [Quick Start](#-quick-start)
- [Contribute](#-contribute)
- [Maintainers](#-maintainers)
- [License](#-copyright)

### Installation
* Install treeplot from PyPI (recommended). treeplot is compatible with Python 3.6+ and runs on Linux, MacOS X and Windows. 
* It is distributed under the MIT license.

#### Quick Start
```
pip install treeplot
```

* Alternatively, install treeplot from the GitHub source:
```bash
git clone https://github.com/erdogant/treeplot.git
cd treeplot
python setup.py install
```  

#### Import treeplot package
```python
import treeplot
```

#### Example RandomForest:
```python
# Load example dataset
X,y = treeplot.import_example()
# Learn model
model = RandomForestClassifier(n_estimators=100, max_depth=2, random_state=0).fit(X, y)
# Make plot
ax = treeplot.plot(model)

# or alternatively if you have more parameters to specify:
ax = treeplot.randomforest(model, export='pdf')
```

#### Example XGboost:
```python
# Load example dataset
X,y = treeplot.import_example()
# Learn model
model = XGBClassifier(n_estimators=100, max_depth=2, random_state=0).fit(X, y)
# Make plot
ax = treeplot.plot(model)

# or alternatively if you have more parameters to specify:
ax = treeplot.xgboost(model, plottype='vertical')
```


#### Maintainers
* Erdogan Taskesen, github: [erdogant](https://github.com/erdogant)

#### Contribute
* Contributions are welcome.

#### Licence
See [LICENSE](LICENSE) for details.

#### Donation
* This work is created and maintained in my free time. Contributions of any kind are very appreciated. <a href="https://erdogant.github.io/donate/?currency=USD&amount=5">Sponsering</a> is also possible.



