pdprpr 0.4.0

Pdprpr preprocesses pandas objects (DataFrame, Series) for machine learning input.

# pdprpr

Pdprpr preprocesses pandas objects (DataFrame, Series) for machine learning input.

## Usage

Assume you have this DataFrame to be preprocessed:

```python
from pandas import DataFrame

df = DataFrame({
'num': [1, 3, float('nan')], # numerical feature to be scaled in [0, 1]
'cat': ['P', 'Q', 'R'], # categorical feature to be transformted to dummy var
'bin': [0, 0, 1], # binary (true/false) feature
}, columns =['num', 'cat', 'bin'])
# num cat bin
# 0 1.0 P 0
# 1 3.0 Q 0
# 2 NaN R 1
```

You can define preprocessing settings in JSON-like format:

```yaml
# preprocessing.yml
- name: num
kind: numerical

- name: cat
kind: categorical

- name: bin
kind: binary
```

Then `DataFramePreprocessor` instance can be created with them:

```python
import yaml

with open('preprocessing.yml') as f:
settings = yaml.load(f)

from pdprpr import DataFramePreprocessor

processor = DataFramePreprocessor(settings)
```

Finary you can use it to preprocess your DataFrame:

```python
processor.process(df)
# num/value cat/P cat/Q cat/R bin/False bin/True
# 0 0.0 1 0 0 1 0
# 1 1.0 0 1 0 1 0
# 2 NaN 0 0 1 0 1
```

For more options please see [tests](./tests/) untill docs are available...