sklearn.tables#

Submodule of khiops.sklearn

Classes for handling diverse data tables

Functions#

`get_khiops_type`	Translates a numpy type to a Khiops dictionary type
`read_internal_data_table`	Reads into a DataFrame a data table file with the internal format settings
`write_internal_data_table`	Writes a DataFrame to data table file with the internal format settings

Classes#

`Dataset`	A representation of a dataset
`DatasetTable`	A generic dataset table
`FileTable`	A table representing a delimited text file
`NumpyTable`	Table encapsulating (X,y) pair with types (ndarray, ndarray)
`PandasTable`	Table encapsulating (X,y) pair with types (pandas.DataFrame, pandas.Series)

class khiops.sklearn.tables.Dataset(X, y=None, categorical_target=True, key=None)#

Bases: object

A representation of a dataset

Parameters:

Xpandas.DataFrame or dict (Deprecated types: tuple and list)

Either:

A single dataframe
A dict dataset specification

ypandas.Series or str, optional

The target column.

categorical_targetbool, default True

True if the vector y should be considered as a categorical variable. If False it is considered as numeric. Ignored if y is None.

keystr

The name of the key column for all tables. Deprecated: Will be removed in pyKhiops 11.

copy()#

Creates a copy of the dataset

Referenced dataframes in tables are copied as references

create_khiops_dictionary_domain()#

Creates a Khiops dictionary domain representing this dataset

Returns:

DictionaryDomain: The dictionary domain object representing this dataset

create_table_files_for_khiops(target_dir, sort=True)#

Prepares the tables of the dataset to be used by Khiops

If this is a multi-table dataset it will create sorted copies the tables.

Parameters:

target_dirstr: The directory where the sorted tables will be created

Returns:

tuple

A tuple containing:

The path of the main table
A dictionary containing the relation [table-name -> file-path] for the secondary tables. The dictionary is empty for monotable datasets.

is_in_memory()#

Tests whether the dataset is in memory

A dataset is in memory if it is constituted either of only pandas.DataFrame tables or numpy.ndarray tables.

Returns:

bool: True if the dataset is constituted of pandas.DataFrame tables.

is_multitable()#

Tests whether the dataset is a multi-table one

Returns:

bool: True if the dataset is multi-table.

property target_column_type#: The target column’s type

class khiops.sklearn.tables.DatasetTable(name, categorical_target=True, key=None)#

Bases: ABC

A generic dataset table

check_key()#: Checks that the key columns exist

create_khiops_dictionary()#

Creates a Khiops dictionary representing this table

Returns:

Dictionary:: The Khiops Dictionary object describing this table’s schema

abstract create_table_file_for_khiops(output_dir, sort=True)#: Creates a copy of the table at the specified directory

n_features()#

Returns the number of features of the table

The target column does not count.

class khiops.sklearn.tables.FileTable(name, path, target_column_id=None, categorical_target=True, key=None, sep='\t', header=True)#

Bases: DatasetTable

A table representing a delimited text file

Parameters:

namestr: Name for the table.
pathstr: Path of the file containing the table.
sepstr, optional: Field separator character. If not specified it will be inferred from the file.
headerbool, optional: Indicates if the table
keylist-like of str, optional: The names of the columns composing the key
target_column_idstr, optional: Name of the target variable column.
categorical_targetbool, default True.: True if the target column is categorical.

create_table_file_for_khiops(output_dir, sort=True)#: Creates a copy of the table at the specified directory

class khiops.sklearn.tables.NumpyTable(name, array, key=None, target_column=None, categorical_target=True)#

Bases: DatasetTable

Table encapsulating (X,y) pair with types (ndarray, ndarray)

Parameters:

namestr: Name for the table.
arrayarray-like of shape (n_samples, n_features_in): The data frame to be encapsulated.
key:external:term`array-like` of int, optional: The names of the columns composing the key
target_columnarray-like of shape (n_samples,) , optional: The series representing the target column.
categorical_targetbool, default True.: True if the target column is categorical.

create_table_file_for_khiops(output_dir, sort=True)#: Creates a copy of the table at the specified directory

get_khiops_variable_name(column_id)#: Return the khiops variable name associated to a column id

class khiops.sklearn.tables.PandasTable(name, dataframe, key=None, target_column=None, categorical_target=True)#

Bases: DatasetTable

Table encapsulating (X,y) pair with types (pandas.DataFrame, pandas.Series)

Parameters:

namestr: Name for the table.
dataframepandas.DataFrame: The data frame to be encapsulated.
keylist-like of str, optional: The names of the columns composing the key
target_columnarray-like, optional: The array containing the target column.
categorical_targetbool, default True.: True if the target column is categorical.

create_table_file_for_khiops(output_dir, sort=True)#: Creates a copy of the table at the specified directory

get_khiops_variable_name(column_id)#: Return the khiops variable name associated to a column id

khiops.sklearn.tables.get_khiops_type(numpy_type)#

Translates a numpy type to a Khiops dictionary type

Parameters:

numpy_typenumpy.dtype:: Numpy type of the column

Returns:

str: Khiops type name. Either “Categorical”, “Numerical” or “Timestamp”

khiops.sklearn.tables.read_internal_data_table(file_path_or_stream)#

Reads into a DataFrame a data table file with the internal format settings

The table is read with the following settings:

Use tab as separator
Read the column names from the first line
Use ‘”’ as quote character
Use csv.QUOTE_MINIMAL
double quoting enabled (quotes within quotes can be escaped with ‘””’)
UTF-8 encoding

Parameters:

file_path_or_streamstr or file object: The path of the internal data table file to be read or a readable file object.

Returns:

pandas.DataFrame: The dataframe representation.

khiops.sklearn.tables.write_internal_data_table(dataframe, file_path_or_stream)#

Writes a DataFrame to data table file with the internal format settings

The table is written with the following settings:

Use tab as separator
Write the column names on the first line
Use ‘”’ as quote character
Use csv.QUOTE_MINIMAL
double quoting enabled (quotes within quotes can be escaped with ‘””’)
UTF-8 encoding
The index is not written

Parameters:

dataframepandas.DataFrame: The dataframe to write.
file_path_or_streamstr or file object: The path of the internal data table file to be written or a writable file object.