great_expectations.profile.basic_dataset_profiler
¶
Module Contents¶
Classes¶
BasicDatasetProfilerBase provides basic logic of inferring the type and the cardinality of columns |
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BasicDatasetProfiler is inspired by the beloved pandas_profiling project. |
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great_expectations.profile.basic_dataset_profiler.
OperationalError
¶
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great_expectations.profile.basic_dataset_profiler.
logger
¶
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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.
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INT_TYPE_NAMES
¶
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FLOAT_TYPE_NAMES
¶
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STRING_TYPE_NAMES
¶
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BOOLEAN_TYPE_NAMES
¶
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DATETIME_TYPE_NAMES
¶
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classmethod
_get_column_type
(cls, df, column)¶
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classmethod
_get_column_cardinality
(cls, df, column)¶
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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.
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classmethod
_profile
(cls, dataset, configuration=None)¶
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classmethod