woodwork.table_accessor.WoodworkTableAccessor

class woodwork.table_accessor.WoodworkTableAccessor(dataframe)

__init__(dataframe)

Methods

__init__(dataframe)
add_semantic_tags(semantic_tags)	Adds specified semantic tags to columns, updating the Woodwork typing information.
dependence([measures, num_bins, nrows, ...])	Calculates dependence measures between all pairs of columns in the DataFrame that support measuring dependence.
dependence_dict([measures, num_bins, nrows, ...])	Calculates dependence measures between all pairs of columns in the DataFrame that support measuring dependence.
describe([include, callback, results_callback])	Calculates statistics for data contained in the DataFrame.
describe_dict([include, callback, ...])	Calculates statistics for data contained in the DataFrame.
drop(columns[, inplace])	Drop specified columns from a DataFrame.
get_valid_mi_columns([include_index, ...])	Retrieves a list of columns from the DataFrame with valid Logical Types that support mutual information.
infer_temporal_frequencies([...])	Infers the observation frequency (daily, biweekly, yearly, etc) of each temporal column
init(**kwargs)	Initializes Woodwork typing information for a DataFrame with a partial schema.
init_with_full_schema(schema[, validate])	Initializes Woodwork typing information for a DataFrame with a complete schema.
init_with_partial_schema([schema, index, ...])	Initializes Woodwork typing information for a DataFrame with a partial schema.
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.
pearson_correlation([nrows, include_index, ...])	Calculates Pearson correlation coefficient between all pairs of columns in the DataFrame that support correlation.
pearson_correlation_dict([nrows, ...])	Calculates Pearson correlation coefficient between all pairs of columns in the DataFrame that support correlation.
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[, inplace])	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, exclude, return_schema])	Create a DataFrame with Woodwork typing information initialized that includes only columns whose Logical Type and semantic tags match conditions specified in the list of types and tags to include or exclude.
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.
spearman_correlation([nrows, include_index, ...])	Calculates Spearman correlation coefficient between all pairs of columns in the DataFrame that support correlation.
spearman_correlation_dict([nrows, ...])	Calculates Spearman correlation coefficient between all pairs of columns in the DataFrame that support correlation.
to_dictionary()	Get a dictionary representation of the Woodwork typing information.
to_disk(path[, format, filename, ...])	Write Woodwork table to disk in the format specified by format, location specified by path.
validate_logical_types([return_invalid_values])	Validates the dataframe based on the logical types.
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
metadata	Metadata of the DataFrame
name	Name of the DataFrame
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.
use_standard_tags	A dictionary containing the use_standard_tags setting for each column in the table