https://github.com/shunk031/allennlp-dataframe-mapper

AllenNLP integration for sklearn-pandas
https://github.com/shunk031/allennlp-dataframe-mapper

allennlp machine-learning pipeline sklearn sklearn-pandas

Last synced: 7 months ago
JSON representation

AllenNLP integration for sklearn-pandas

• Host: GitHub
• URL: https://github.com/shunk031/allennlp-dataframe-mapper
• Owner: shunk031
• License: mit
• Created: 2020-10-20T08:17:52.000Z (almost 5 years ago)
• Default Branch: master
• Last Pushed: 2022-09-01T04:38:06.000Z (about 3 years ago)
• Last Synced: 2025-02-17T17:03:52.596Z (8 months ago)
• Topics: allennlp, machine-learning, pipeline, sklearn, sklearn-pandas
• Language: Python
• Homepage:
• Size: 435 KB
• Stars: 1
• Watchers: 3
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# AllenNLP integration for sklearn-pandas

![CI](https://github.com/shunk031/allennlp-dataframe-mapper/workflows/CI/badge.svg?branch=master)

![Release](https://github.com/shunk031/allennlp-dataframe-mapper/workflows/Release/badge.svg)

![Python](https://img.shields.io/badge/python-3.7%20%7C%203.8-blue?logo=python)

[![PyPI](https://img.shields.io/pypi/v/allennlp-dataframe-mapper.svg)](https://pypi.python.org/pypi/allennlp-dataframe-mapper)

`allennlp-dataframe-mapper` is a Python library that provides [AllenNLP](https://github.com/allenai/allennlp) integration for [sklearn-pandas](https://github.com/scikit-learn-contrib/sklearn-pandas).

## Installation

Installing the library and dependencies is simple using `pip`.

```sh

$ pip install allennlp-dataframe-mapper

```

## Example

This library enables users to specify the in a jsonnet config file.

Here is an example of the mapper for a famous [iris dataset](https://archive.ics.uci.edu/ml/datasets/iris).

### Config

`allennlp-dataframe-mapper` is specified the transformations of the mapper in `jsonnet` config file like following `mapper_iris.jsonnet`:

```json

{

    "type": "default",

    "features": [

        [["sepal length (cm)"], null],

        [["sepal width (cm)"], null],

        [["petal length (cm)"], null],

        [["petal width (cm)"], null],

        [["species"], [{"type": "flatten"}, {"type": "label-encoder"}]],

    ],

    "df_out": true,

}

```

### Mapper

The mapper takes a param of transformations from the config file.

We can use the `fit_transform` shortcut to both fit the mapper and see what transformed data.

```python

from allennlp.common import Params

from allennlp_dataframe_mapper import DataFrameMapper

params = Params.from_file("mapper_iris.jsonnet")

mapper = DataFrameMapper.from_params(params=params)

print(mapper)

# DataFrameMapper(df_out=True,

#                 features=[(['sepal length (cm)'], None, {}),

#                           (['sepal width (cm)'], None, {}),

#                           (['petal length (cm)'], None, {}),

#                           (['petal width (cm)'], None, {}),

#                           (['species'], [FlattenTransformer(), LabelEncoder()], {})])

mapper.fit_transform(df)

```

## License

MIT