woodwork.table_accessor.WoodworkTableAccessor

class woodwork.table_accessor.WoodworkTableAccessor(dataframe)

__init__(dataframe)

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__(dataframe)	Initialize self.
add_semantic_tags(semantic_tags)	Adds specified semantic tags to columns, updating the Woodwork typing information.
describe([include])	Calculates statistics for data contained in the DataFrame.
describe_dict([include])	Calculates statistics for data contained in the DataFrame.
drop(columns)	Drop specified columns from a DataFrame.
init([index, time_index, logical_types, …])	Initializes Woodwork typing information for a DataFrame.
mutual_information([num_bins, nrows, …])	Calculates mutual information between all pairs of columns in the DataFrame that support mutual information.
mutual_information_dict([num_bins, nrows, …])	Calculates mutual information between all pairs of columns in the DataFrame that support mutual information.
pop(column_name)	Return a Series with Woodwork typing information and remove it from the DataFrame.
remove_semantic_tags(semantic_tags)	Remove the semantic tags for any column names in the provided semantic_tags dictionary, updating the Woodwork typing information.
rename(columns)	Renames columns in a DataFrame, maintaining Woodwork typing information.
reset_semantic_tags([columns, retain_index_tags])	Reset the semantic tags for the specified columns to the default values.
select(include)	Create a DataFrame with Woodwork typing information initialized that includes only columns whose Logical Type and semantic tags are specified in the list of types and tags to include.
set_index(new_index)	Sets the index column of the DataFrame.
set_time_index(new_time_index)	Set the time index.
set_types([logical_types, semantic_tags, …])	Update the logical type and semantic tags for any columns names in the provided types dictionaries, updating the Woodwork typing information for the DataFrame.
to_csv(path[, sep, encoding, engine, …])	Write Woodwork table to disk in the CSV format, location specified by path.
to_dictionary()	Get a dictionary representation of the Woodwork typing information.
to_parquet(path[, compression, profile_name])	Write Woodwork table to disk in the parquet format, location specified by path.
to_pickle(path[, compression, profile_name])	Write Woodwork table to disk in the pickle format, location specified by path.
value_counts([ascending, top_n, dropna])	Returns a list of dictionaries with counts for the most frequent values in each column (only

Attributes

iloc	Integer-location based indexing for selection by position.
index	The index column for the table
loc	Access a group of rows by label(s) or a boolean array.
logical_types	A dictionary containing logical types for each column
physical_types	A dictionary containing physical types for each column
schema	A copy of the Woodwork typing information for the DataFrame.
semantic_tags	A dictionary containing semantic tags for each column
time_index	The time index column for the table
types	DataFrame containing the physical dtypes, logical types and semantic tags for the Schema.

API Reference woodwork.table_accessor.WoodworkTableAccessor.add_semantic_tags