great_expectations.profile.basic_dataset_profiler

Module Contents

Classes

BasicDatasetProfilerBase()	BasicDatasetProfilerBase provides basic logic of inferring the type and the cardinality of columns
BasicDatasetProfiler()	BasicDatasetProfiler is inspired by the beloved pandas_profiling project.

great_expectations.profile.basic_dataset_profiler.OperationalError

great_expectations.profile.basic_dataset_profiler.logger

class great_expectations.profile.basic_dataset_profiler.BasicDatasetProfilerBase

Bases: great_expectations.profile.base.DatasetProfiler

BasicDatasetProfilerBase provides basic logic of inferring the type and the cardinality of columns that is used by the dataset profiler classes that extend this class.

INT_TYPE_NAMES

FLOAT_TYPE_NAMES

STRING_TYPE_NAMES

BOOLEAN_TYPE_NAMES

DATETIME_TYPE_NAMES

classmethod _get_column_type(cls, df, column)

classmethod _get_column_cardinality(cls, df, column)

class great_expectations.profile.basic_dataset_profiler.BasicDatasetProfiler

Bases: great_expectations.profile.basic_dataset_profiler.BasicDatasetProfilerBase

BasicDatasetProfiler is inspired by the beloved pandas_profiling project.

The profiler examines a batch of data and creates a report that answers the basic questions most data practitioners would ask about a dataset during exploratory data analysis. The profiler reports how unique the values in the column are, as well as the percentage of empty values in it. Based on the column’s type it provides a description of the column by computing a number of statistics, such as min, max, mean and median, for numeric columns, and distribution of values, when appropriate.

classmethod _profile(cls, dataset, configuration=None)