featuretools.EntitySet¶
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class
featuretools.
EntitySet
(id=None, entities=None, relationships=None)[source]¶ Stores all actual data for a entityset
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id
¶
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entity_dict
¶
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relationships
¶
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time_type
¶
- Properties:
metadata
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__init__
(id=None, entities=None, relationships=None)[source]¶ Creates EntitySet
- Parameters
id (str) – Unique identifier to associate with this instance
entities (dict[str -> tuple(pd.DataFrame, str, str, dict[str -> Variable])]) – dictionary of entities. Entries take the format {entity id -> (dataframe, id column, (time_index), (variable_types), (make_index))}. Note that time_index, variable_types and make_index are optional.
relationships (list[(str, str, str, str)]) – List of relationships between entities. List items are a tuple with the format (parent entity id, parent variable, child entity id, child variable).
Example
entities = { "cards" : (card_df, "id"), "transactions" : (transactions_df, "id", "transaction_time") } relationships = [("cards", "id", "transactions", "card_id")] ft.EntitySet("my-entity-set", entities, relationships)
Methods
__init__
([id, entities, relationships])Creates EntitySet
add_interesting_values
([max_values, verbose])Find interesting values for categorical variables, to be used to generate “where” clauses
add_last_time_indexes
([updated_entities])Calculates the last time index values for each entity (the last time an instance or children of that instance were observed).
add_relationship
(relationship)Add a new relationship between entities in the entityset
add_relationships
(relationships)Add multiple new relationships to a entityset
concat
(other[, inplace])Combine entityset with another to create a new entityset with the combined data of both entitysets.
entity_from_dataframe
(entity_id, dataframe)Load the data for a specified entity from a Pandas DataFrame.
find_backward_paths
(start_entity_id, …)Generator which yields all backward paths between a start and goal entity.
find_forward_paths
(start_entity_id, …)Generator which yields all forward paths between a start and goal entity.
get_backward_entities
(entity_id[, deep])Get entities that are in a backward relationship with entity
get_backward_relationships
(entity_id)get relationships where entity “entity_id” is the parent.
get_forward_entities
(entity_id[, deep])Get entities that are in a forward relationship with entity
get_forward_relationships
(entity_id)Get relationships where entity “entity_id” is the child
has_unique_forward_path
(start_entity_id, …)Is the forward path from start to end unique?
normalize_entity
(base_entity_id, …[, …])Create a new entity and relationship from unique values of an existing variable.
plot
([to_file])Create a UML diagram-ish graph of the EntitySet.
reset_data_description
()to_csv
(path[, sep, encoding, engine, …])Write entityset to disk in the csv format, location specified by path.
to_dictionary
()to_parquet
(path[, engine, compression, …])Write entityset to disk in the parquet format, location specified by path.
to_pickle
(path[, compression, profile_name])Write entityset in the pickle format, location specified by path.
Attributes
entities
metadata
Returns the metadata for this EntitySet.
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