featuretools.EntitySet#
- class featuretools.EntitySet(id=None, dataframes=None, relationships=None)[source]#
Stores all actual data and typing information for an entityset
- id#
- dataframe_dict#
- relationships#
- time_type#
- Properties:
metadata
- __init__(id=None, dataframes=None, relationships=None)[source]#
Creates EntitySet
- Parameters:
id (str) – Unique identifier to associate with this instance
dataframes (dict[str -> tuple(DataFrame, str, str, dict[str -> str/Woodwork.LogicalType], dict[str->str/set], boolean)]) – Dictionary of DataFrames. Entries take the format {dataframe name -> (dataframe, index column, time_index, logical_types, semantic_tags, make_index)}. Note that only the dataframe is required. If a Woodwork DataFrame is supplied, any other parameters will be ignored.
relationships (list[(str, str, str, str)]) – List of relationships between dataframes. List items are a tuple with the format (parent dataframe name, parent column, child dataframe name, child column).
Example
dataframes = { "cards" : (card_df, "id"), "transactions" : (transactions_df, "id", "transaction_time") } relationships = [("cards", "id", "transactions", "card_id")] ft.EntitySet("my-entity-set", dataframes, relationships)
Methods
__init__
([id, dataframes, relationships])Creates EntitySet
add_dataframe
(dataframe[, dataframe_name, ...])Add a DataFrame to the EntitySet with Woodwork typing information.
add_interesting_values
([max_values, ...])Find or set interesting values for categorical columns, to be used to generate "where" clauses
add_last_time_indexes
([updated_dataframes])Calculates the last time index values for each dataframe (the last time an instance or children of that instance were observed).
add_relationship
([parent_dataframe_name, ...])Add a new relationship between dataframes 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.
find_backward_paths
(start_dataframe_name, ...)Generator which yields all backward paths between a start and goal dataframe.
find_forward_paths
(start_dataframe_name, ...)Generator which yields all forward paths between a start and goal dataframe.
get_backward_dataframes
(dataframe_name[, deep])Get dataframes that are in a backward relationship with dataframe
get_backward_relationships
(dataframe_name)get relationships where dataframe "dataframe_name" is the parent.
get_forward_dataframes
(dataframe_name[, deep])Get dataframes that are in a forward relationship with dataframe
get_forward_relationships
(dataframe_name)Get relationships where dataframe "dataframe_name" is the child
has_unique_forward_path
(...)Is the forward path from start to end unique?
normalize_dataframe
(base_dataframe_name, ...)Create a new dataframe and relationship from unique values of an existing column.
plot
([to_file])Create a UML diagram-ish graph of the EntitySet.
query_by_values
(dataframe_name, instance_vals)Query instances that have column with given value
replace_dataframe
(dataframe_name, df[, ...])Replace the internal dataframe of an EntitySet table, keeping Woodwork typing information the same.
reset_data_description
()set_secondary_time_index
(dataframe_name, ...)Set the secondary time index for a dataframe in the EntitySet using its dataframe name.
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
dataframes
metadata
Returns the metadata for this EntitySet.