Column Profile Compilers

For generating a report.

class dataprofiler.profilers.column_profile_compilers.BaseCompiler(df_series: Optional[pandas.core.series.Series] = None, options: Optional[dataprofiler.profilers.profiler_options.StructuredOptions] = None, pool: Optional[multiprocessing.pool.Pool] = None)

Bases: Generic[dataprofiler.profilers.column_profile_compilers.BaseCompilerT]

Abstract class for generating a report.

Initialize BaseCompiler object.

abstract report(remove_disabled_flag: bool = False) → dict

Return report.

Parameters

remove_disabled_flag (boolean) – flag to determine if disabled options should be excluded in report.

property profile: dict

Return the profile of the column.

diff(other: dataprofiler.profilers.column_profile_compilers.BaseCompilerT, options: Optional[dict] = None) → dict

Find the difference between 2 compilers and returns the report.

Parameters

other (BaseCompiler) – profile compiler finding the difference with this one.

Returns

difference of the profiles

Return type

dict

update_profile(df_series: Series, pool: Pool = None) → BaseCompiler | None

Update the profiles from the data frames.

Parameters

• df_series (pandas.core.series.Series) – a given column, assume df_series in str

• pool (multiprocessing.Pool) – pool to utilized for multiprocessing

Returns

Self

Return type

BaseCompiler

classmethod load_from_dict(data, config: dict | None = None) → BaseCompiler

Parse attribute from json dictionary into self.

Parameters

• data (dict[string, Any]) – dictionary with attributes and values.

• config (Dict | None) – config for loading column profiler params from dictionary

Returns

Compiler with attributes populated.

Return type

BaseCompiler

class dataprofiler.profilers.column_profile_compilers.ColumnPrimitiveTypeProfileCompiler(df_series: Optional[pandas.core.series.Series] = None, options: Optional[dataprofiler.profilers.profiler_options.StructuredOptions] = None, pool: Optional[multiprocessing.pool.Pool] = None)

Bases: dataprofiler.profilers.column_profile_compilers.BaseCompiler[ColumnPrimitiveTypeProfileCompiler]

For generating ordered column profile reports.

Initialize BaseCompiler object.

report(remove_disabled_flag: bool = False) → dict

Return report.

Parameters

remove_disabled_flag (boolean) – flag to determine if disabled options should be excluded in report.

property profile: dict

Return the profile of the column.

property selected_data_type: str | None

Find the selected data_type in a primitive compiler.

Returns

name of the selected data type

Return type

str

diff(other: dataprofiler.profilers.column_profile_compilers.ColumnPrimitiveTypeProfileCompiler, options: Optional[dict] = None) → dict

Find the difference between 2 compilers and returns the report.

Parameters

other (ColumnPrimitiveTypeProfileCompiler) – profile compiler finding the difference with this one.

Returns

difference of the profiles

Return type

dict

classmethod load_from_dict(data, config: dict | None = None) → BaseCompiler

Parse attribute from json dictionary into self.

Parameters

• data (dict[string, Any]) – dictionary with attributes and values.

• config (Dict | None) – config for loading column profiler params from dictionary

Returns

Compiler with attributes populated.

Return type

BaseCompiler

update_profile(df_series: Series, pool: Pool = None) → BaseCompiler | None

Update the profiles from the data frames.

Parameters

• df_series (pandas.core.series.Series) – a given column, assume df_series in str

• pool (multiprocessing.Pool) – pool to utilized for multiprocessing

Returns

Self

Return type

BaseCompiler

class dataprofiler.profilers.column_profile_compilers.ColumnStatsProfileCompiler(df_series: Optional[pandas.core.series.Series] = None, options: Optional[dataprofiler.profilers.profiler_options.StructuredOptions] = None, pool: Optional[multiprocessing.pool.Pool] = None)

Bases: dataprofiler.profilers.column_profile_compilers.BaseCompiler[ColumnStatsProfileCompiler]

For generating OrderColumn and CategoricalColumn reports.

Initialize BaseCompiler object.

report(remove_disabled_flag: bool = False) → dict

Return report.

Parameters

remove_disabled_flag (boolean) – flag to determine if disabled options should be excluded in report.

diff(other: dataprofiler.profilers.column_profile_compilers.ColumnStatsProfileCompiler, options: Optional[dict] = None) → dict

Find the difference between 2 compilers and returns the report.

Parameters

other (ColumnStatsProfileCompiler) – profile compiler finding the difference with this one.

Returns

difference of the profiles

Return type

dict

classmethod load_from_dict(data, config: dict | None = None) → BaseCompiler

Parse attribute from json dictionary into self.

Parameters

• data (dict[string, Any]) – dictionary with attributes and values.

• config (Dict | None) – config for loading column profiler params from dictionary

Returns

Compiler with attributes populated.

Return type

BaseCompiler

property profile: dict

Return the profile of the column.

update_profile(df_series: Series, pool: Pool = None) → BaseCompiler | None

Update the profiles from the data frames.

Parameters

• df_series (pandas.core.series.Series) – a given column, assume df_series in str

• pool (multiprocessing.Pool) – pool to utilized for multiprocessing

Returns

Self

Return type

BaseCompiler

class dataprofiler.profilers.column_profile_compilers.ColumnDataLabelerCompiler(df_series: Optional[pandas.core.series.Series] = None, options: Optional[dataprofiler.profilers.profiler_options.StructuredOptions] = None, pool: Optional[multiprocessing.pool.Pool] = None)

Bases: dataprofiler.profilers.column_profile_compilers.BaseCompiler[ColumnDataLabelerCompiler]

For generating DataLabelerColumn report.

Initialize BaseCompiler object.

report(remove_disabled_flag: bool = False) → dict

Return report.

Parameters

remove_disabled_flag (boolean) – flag to determine if disabled options should be excluded in report.

diff(other: dataprofiler.profilers.column_profile_compilers.ColumnDataLabelerCompiler, options: Optional[dict] = None) → dict

Find the difference between 2 compilers and return the report.

Parameters

• other (ColumnDataLabelerCompiler) – profile compiler finding the difference with this one.

• options (dict) – options to change results of the difference

Returns

difference of the profiles

Return type

dict

classmethod load_from_dict(data, config: dict | None = None) → BaseCompiler

Parse attribute from json dictionary into self.

Parameters

• data (dict[string, Any]) – dictionary with attributes and values.

• config (Dict | None) – config for loading column profiler params from dictionary

Returns

Compiler with attributes populated.

Return type

BaseCompiler

property profile: dict

Return the profile of the column.

update_profile(df_series: Series, pool: Pool = None) → BaseCompiler | None

Update the profiles from the data frames.

Parameters

• df_series (pandas.core.series.Series) – a given column, assume df_series in str

• pool (multiprocessing.Pool) – pool to utilized for multiprocessing

Returns

Self

Return type

BaseCompiler

class dataprofiler.profilers.column_profile_compilers.UnstructuredCompiler(df_series: Optional[pandas.core.series.Series] = None, options: Optional[dataprofiler.profilers.profiler_options.StructuredOptions] = None, pool: Optional[multiprocessing.pool.Pool] = None)

Bases: dataprofiler.profilers.column_profile_compilers.BaseCompiler[UnstructuredCompiler]

For generating TextProfiler and UnstructuredLabelerProfile reports.

Initialize BaseCompiler object.

report(remove_disabled_flag: bool = False) → dict

Report profile attrs of class and potentially pop val from self.profile.

diff(other: dataprofiler.profilers.column_profile_compilers.UnstructuredCompiler, options: Optional[dict] = None) → dict

Find the difference between 2 compilers and return the report.

Parameters

• other (UnstructuredCompiler) – profile compiler finding the difference with this one.

• options (dict) – options to impact the results of the diff

Returns

difference of the profiles

Return type

dict

classmethod load_from_dict(data, config: dict | None = None) → BaseCompiler

Parse attribute from json dictionary into self.

Parameters

• data (dict[string, Any]) – dictionary with attributes and values.

• config (Dict | None) – config for loading column profiler params from dictionary

Returns

Compiler with attributes populated.

Return type

BaseCompiler

property profile: dict

Return the profile of the column.

update_profile(df_series: Series, pool: Pool = None) → BaseCompiler | None

Update the profiles from the data frames.

Parameters

• df_series (pandas.core.series.Series) – a given column, assume df_series in str

• pool (multiprocessing.Pool) – pool to utilized for multiprocessing

Returns

Self

Return type

BaseCompiler