actableai.data_imputation package

Subpackages

• actableai.data_imputation.auto_fixer package
  • Submodules
  • actableai.data_imputation.auto_fixer.auto_fixer module
  • actableai.data_imputation.auto_fixer.auto_gluon_fixer module
  • actableai.data_imputation.auto_fixer.datetime_fixer module
  • actableai.data_imputation.auto_fixer.errors module
  • actableai.data_imputation.auto_fixer.fix_info module
  • actableai.data_imputation.auto_fixer.helper module
  • actableai.data_imputation.auto_fixer.misplaced_refiner module
  • actableai.data_imputation.auto_fixer.neighbor_fixer module
  • actableai.data_imputation.auto_fixer.refiner module
  • actableai.data_imputation.auto_fixer.single_category_fixer module
  • actableai.data_imputation.auto_fixer.strategy module
  • actableai.data_imputation.auto_fixer.validation_refiner module
  • Module contents
• actableai.data_imputation.config package
  • Submodules
  • actableai.data_imputation.config.config module
  • Module contents
• actableai.data_imputation.data package
  • Submodules
  • actableai.data_imputation.data.data_frame module
  • actableai.data_imputation.data.loader module
  • Module contents
• actableai.data_imputation.error_detector package
  • Submodules
  • actableai.data_imputation.error_detector.base_error_detector module
  • actableai.data_imputation.error_detector.cell_erros module
  • actableai.data_imputation.error_detector.column_format module
  • actableai.data_imputation.error_detector.constraint module
  • actableai.data_imputation.error_detector.error_detector module
  • actableai.data_imputation.error_detector.match_condition module
  • actableai.data_imputation.error_detector.misplaced_detector module
  • actableai.data_imputation.error_detector.null_detector module
  • actableai.data_imputation.error_detector.rule_parser module
  • actableai.data_imputation.error_detector.smart_column_selector module
  • actableai.data_imputation.error_detector.validation_constraints_checker module
  • actableai.data_imputation.error_detector.validation_detector module
  • Module contents
• actableai.data_imputation.evaluate package
  • Submodules
  • actableai.data_imputation.evaluate.evaluate module
  • Module contents
• actableai.data_imputation.meta package
  • Submodules
  • actableai.data_imputation.meta.column module
  • actableai.data_imputation.meta.types module
  • Module contents
• actableai.data_imputation.processor package
  • Submodules
  • actableai.data_imputation.processor.categories_data_processor module
  • actableai.data_imputation.processor.processor module
  • Module contents
• actableai.data_imputation.type_recon package
  • Submodules
  • actableai.data_imputation.type_recon.dtype_detector module
  • actableai.data_imputation.type_recon.errors module
  • actableai.data_imputation.type_recon.helper module
  • actableai.data_imputation.type_recon.regex_consts module
  • actableai.data_imputation.type_recon.type_detector module
  • Module contents
• actableai.data_imputation.utils package
  • Submodules
  • actableai.data_imputation.utils.list_utils module
  • actableai.data_imputation.utils.memory module
  • Module contents

Submodules

actableai.data_imputation.correlation_calculator module

class actableai.data_imputation.correlation_calculator.CorrelationCalculator

Bases: object

calculate_correlations_for_all_column_pairs(df: pandas.core.frame.DataFrame) → pandas.core.frame.DataFrame

clear()

most_correlate_columns(df: pandas.core.frame.DataFrame, col: str, top: int) → List[str]

actableai.data_imputation.data_imputation module

actableai.data_imputation.data_imputation.data_imputation(df, rules='', impute_nulls=True)

actableai.data_imputation.main module

Module contents

class actableai.data_imputation.ColumnType(value)

Bases: enum.Enum

An enumeration.

Category = 'category'

Complex = 'complex'

Float = 'float'

Id = 'id'

Integer = 'integer'

NULL = 'null'

NumWithTag = 'num_with_tag'

Percentage = 'percentage'

String = 'string'

Temperature = 'temperature'

Text = 'text'

Timestamp = 'timestamp'

Unknown = 'unknown'

class actableai.data_imputation.DataFrame(d: Union[str, pandas.core.frame.DataFrame])

Bases: pandas.core.frame.DataFrame

auto_fix(errors: Optional[actableai.data_imputation.error_detector.cell_erros.CellErrors] = None, *detectors: actableai.data_imputation.error_detector.base_error_detector.BaseErrorDetector) → actableai.data_imputation.data.data_frame.DataFrame

property column_types: actableai.data_imputation.type_recon.type_detector.DfTypes

detect_error(*detectors: actableai.data_imputation.error_detector.base_error_detector.BaseErrorDetector) → actableai.data_imputation.error_detector.cell_erros.CellErrors

enable_debug(enable: bool = True)

property fix_info

property fix_strategy

classmethod from_dict(data, orient='columns', dtype=None, columns=None) → actableai.data_imputation.data.data_frame.DataFrame

Construct DataFrame from dict of array-like or dicts.

Creates DataFrame object from dictionary by columns or by index allowing dtype specification.

Parameters

• data (dict) – Of the form {field : array-like} or {field : dict}.
• orient ({'columns', 'index'}, default 'columns') – The “orientation” of the data. If the keys of the passed dict should be the columns of the resulting DataFrame, pass ‘columns’ (default). Otherwise if the keys should be rows, pass ‘index’.
• dtype (dtype, default None) – Data type to force, otherwise infer.
• columns (list, default None) – Column labels to use when orient='index'. Raises a ValueError if used with orient='columns'.

Return type

DataFrame

See also

DataFrame.from_records

DataFrame from structured ndarray, sequence of tuples or dicts, or DataFrame.

DataFrame

DataFrame object creation using constructor.

Examples

By default the keys of the dict become the DataFrame columns:

>>> data = {'col_1': [3, 2, 1, 0], 'col_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data)
   col_1 col_2
0      3     a
1      2     b
2      1     c
3      0     d

Specify orient='index' to create the DataFrame using dictionary keys as rows:

>>> data = {'row_1': [3, 2, 1, 0], 'row_2': ['a', 'b', 'c', 'd']}
>>> pd.DataFrame.from_dict(data, orient='index')
       0  1  2  3
row_1  3  2  1  0
row_2  a  b  c  d

When using the ‘index’ orientation, the column names can be specified manually:

>>> pd.DataFrame.from_dict(data, orient='index',
...                        columns=['A', 'B', 'C', 'D'])
       A  B  C  D
row_1  3  2  1  0
row_2  a  b  c  d

override_column_type(column: str, column_type: actableai.data_imputation.meta.types.ColumnType)

property possible_column_types: Dict[str, Set[actableai.data_imputation.meta.types.ColumnType]]

class actableai.data_imputation.MisplacedDetector(*, preset_rules: typing.List[actableai.data_imputation.error_detector.column_format.PresetRuleName] = (), customize_rules: actableai.data_imputation.error_detector.column_format.MatchRules = <actableai.data_imputation.error_detector.column_format.MatchRules object>)

Bases: actableai.data_imputation.error_detector.base_error_detector.BaseErrorDetector

detect_cells() → actableai.data_imputation.error_detector.cell_erros.CellErrors

property mentioned_columns: Set[str]

setup(df: pandas.core.frame.DataFrame, dftypes: actableai.data_imputation.type_recon.type_detector.DfTypes)

update_df(df: pandas.core.frame.DataFrame)

class actableai.data_imputation.NullDetector

Bases: actableai.data_imputation.error_detector.base_error_detector.BaseErrorDetector

detect_cells() → actableai.data_imputation.error_detector.cell_erros.CellErrors

class actableai.data_imputation.ValidationDetector(constraints: Optional[actableai.data_imputation.error_detector.constraint.Constraints] = NotImplemented)

Bases: actableai.data_imputation.error_detector.base_error_detector.BaseErrorDetector

property constraints

detect_cells() → actableai.data_imputation.error_detector.cell_erros.CellErrors

classmethod from_constraints(constraints_string: str)

setup_constraints(constraints: actableai.data_imputation.error_detector.constraint.Constraints)