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.

Getting Started

• Install
• Demos
• API Reference

Install

pip install featuretools[autonormalize]

Uninstall

pip uninstall autonormalize

Demos

• Blog Post
• Machine Learning Demo with Featuretools
• Kaggle Liquor Sales Dataset Demo
• Demo with Editing Dependencies
• Kaggle Food Production Dataset Demo

API Reference

auto_entityset

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

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

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

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_dataframeand a new index will be created if any key has more than a single attribute.

Returns:

• entityset (ft.EntitySet) : created EntitySet

normalize_entityset

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

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