Metadata-Version: 2.1
Name: woodwork
Version: 0.0.1
Summary: a two-dimensional data object with labeled axes and typing information
Home-page: https://github.com/FeatureLabs/woodwork/
Author: Alteryx, Inc.
Author-email: support@featurelabs.com
License: BSD 3-clause
Keywords: data science machine learning typing
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.6, <4
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.19.1)
Requires-Dist: pandas (>=1.1.0)

# Woodwork

[![codecov](https://codecov.io/gh/FeatureLabs/woodwork/branch/main/graph/badge.svg?token=KJCKMREBDP)](https://codecov.io/gh/FeatureLabs/woodwork)

DataTable are common data objects to use with Featuretools, EvalML, and general ML. A DataTable object contains the physical, logical, and semantic data types present in the data. In addition, it stores metadata about the data.

## Installation

Clone repo

```bash
git clone https://github.com/FeatureLabs/woodwork.git
cd woodwork
```

Install with pip in editable mode

```bash
python -m pip install -e .
```

## Example

Below is an example of using Woodwork.

```python
from woodwork import DataTable
from woodwork.logical_types import Datetime, Categorical, NaturalLanguage

import pandas as pd

df = pd.read_csv(...)

dt = DataTable(df,
               name='retail', # default to df.name
               index=None,
               time_index=None)

dt.set_types({
    "datetime": Datetime,
    "comments": NaturalLanguage,
    "store_id": Categorical
})
```

## Built at Alteryx Innovation Labs

<a href="https://www.alteryx.com/innovation-labs">
    <img src="https://evalml-web-images.s3.amazonaws.com/alteryx_innovation_labs.png" alt="Alteryx Innovation Labs" />
</a>


