https://github.com/alteryx/autonormalize
python library for automated dataset normalization
https://github.com/alteryx/autonormalize
automatic automatic-normalization normalization
Last synced: 5 months ago
JSON representation
python library for automated dataset normalization
- Host: GitHub
- URL: https://github.com/alteryx/autonormalize
- Owner: alteryx
- License: bsd-3-clause
- Created: 2019-06-26T19:18:25.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2023-07-20T13:19:29.000Z (over 2 years ago)
- Last Synced: 2025-07-22T18:40:39.141Z (6 months ago)
- Topics: automatic, automatic-normalization, normalization
- Language: Python
- Homepage: https://blog.featurelabs.com/automatic-dataset-normalization-for-feature-engineering-in-python/
- Size: 18.8 MB
- Stars: 116
- Watchers: 10
- Forks: 16
- Open Issues: 21
-
Metadata Files:
- Readme: README.md
- Contributing: contributing.md
- License: LICENSE
Awesome Lists containing this project
README
# AutoNormalize
AutoNormalize is a Python library for automated datatable normalization. It allows you to build an `EntitySet` from a single denormalized table and generate features for machine learning using [Featuretools](https://github.com/FeatureLabs/featuretools).
## Getting Started
- [Install](#install)
- [Demos](#demos)
- [API Reference](#api-reference)
## Install
```shell
pip install featuretools[autonormalize]
```
#### Uninstall
```shell
pip uninstall autonormalize
```
## Demos
- [Blog Post](https://blog.featurelabs.com/automatic-dataset-normalization-for-feature-engineering-in-python/)
- [Machine Learning Demo with Featuretools](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/AutoNormalize%20%2B%20FeatureTools%20Demo.ipynb)
- [Kaggle Liquor Sales Dataset Demo](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/Kaggle%20Liquor%20Sales%20Dataset%20Demo.ipynb)
- [Demo with Editing Dependencies](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/Editing%20Dependnecies%20Demo.ipynb)
- [Kaggle Food Production Dataset Demo](https://github.com/FeatureLabs/autonormalize/blob/master/autonormalize/demos/Kaggle%20Food%20%20Dataset%20Demo.ipynb)
## API Reference
### `auto_entityset`
```shell
auto_entityset(df, accuracy=0.98, index=None, name=None, time_index=None)
```
Creates a normalized entityset from a dataframe.
**Arguments:**
- `df` (pd.Dataframe) : the dataframe containing data
- `accuracy` (0 < float <= 1.00; default = 0.98) : the accuracy threshold required in order to conclude a dependency (i.e. with accuracy = 0.98, 0.98 of the rows must hold true the dependency LHS --> RHS)
- `index` (str, optional) : name of column that is intended index of df
- `name` (str, optional) : the name of created EntitySet
- `time_index` (str, optional) : name of time column in the dataframe.
**Returns:**
- `entityset` (ft.EntitySet) : created entity set
### `find_dependencies`
```shell
find_dependencies(df, accuracy=0.98, index=None)
```
Finds dependencies within dataframe with the DFD search algorithm.
**Returns:**
- `dependencies` (Dependencies) : the dependencies found in the data within the contraints provided
### `normalize_dataframe`
```shell
normalize_dataframe(df, dependencies)
```
Normalizes dataframe based on the dependencies given. Keys for the newly created DataFrames can only be columns that are strings, ints, or categories. Keys are chosen according to the priority:
1. shortest lenghts
2. has "id" in some form in the name of an attribute
3. has attribute furthest to left in the table
**Returns:**
- `new_dfs` (list[pd.DataFrame]) : list of new dataframes
### `make_entityset`
```shell
make_entityset(df, dependencies, name=None, time_index=None)
```
Creates a normalized EntitySet from dataframe based on the dependencies given. Keys are chosen in the same fashion as for `normalize_dataframe`and a new index will be created if any key has more than a single attribute.
**Returns:**
- `entityset` (ft.EntitySet) : created EntitySet
### `normalize_entityset`
```shell
normalize_entityset(es, accuracy=0.98)
```
Returns a new normalized `EntitySet` from an `EntitySet` with a single entity.
**Arguments:**
- `es` (ft.EntitySet) : EntitySet with a single entity to normalize
**Returns:**
- `new_es` (ft.EntitySet) : new normalized EntitySet
## Built at Alteryx Innovation Labs
