woodwork.table_accessor.WoodworkTableAccessor¶
- class woodwork.table_accessor.WoodworkTableAccessor(dataframe)[source]¶
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Methods
__init__(dataframe)add_semantic_tags(semantic_tags)Adds specified semantic tags to columns, updating the Woodwork typing information.
describe([include, 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([temporal_columns])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.
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.
Get a dictionary representation of the Woodwork typing information.
to_disk(path[, format, compression, ...])Write Woodwork table to disk in the format specified by 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
Integer-location based indexing for selection by position.
The index column for the table
Access a group of rows by label(s) or a boolean array.
A dictionary containing logical types for each column
Metadata of the DataFrame
Name of the DataFrame
A dictionary containing physical types for each column
A copy of the Woodwork typing information for the DataFrame.
A dictionary containing semantic tags for each column
The time index column for the table
DataFrame containing the physical dtypes, logical types and semantic tags for the schema.
A dictionary containing the use_standard_tags setting for each column in the table