DataQualityTestPreset error with Categorical features

Hi team, first of all - thank you for creating this amazing package for DS/MLEs all over the world! 😃

Describe the bug I am using Evidently to assess the Data Quality of my current and reference pandas dataframe datasets.

But, I see the following message on the AWS SageMaker notebook: ValueError: could not convert string to float: ‘Canteen’ (one of my categories in the features)

I was able to successfully run the Education Dataset mentioned here. Error Message:

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
~/anaconda3/envs/python3/lib/python3.8/site-packages/IPython/core/formatters.py in __call__(self, obj)
    343             method = get_real_method(obj, self.print_method)
    344             if method is not None:
--> 345                 return method()
    346             return None
    347         else:

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/suite/base_suite.py in _repr_html_(self)
    105 
    106     def _repr_html_(self):
--> 107         dashboard_id, dashboard_info, graphs = self._build_dashboard_info()
    108         template_params = TemplateParams(
    109             dashboard_id=dashboard_id, dashboard_info=dashboard_info, additional_graphs=graphs

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/test_suite/test_suite.py in _build_dashboard_info(self)
    126             renderer.color_options = color_options
    127             by_status[test_result.status] = by_status.get(test_result.status, 0) + 1

--> 128             test_results.append(renderer.render_html(test))
    129 
    130         summary_widget = BaseWidgetInfo(

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/tests/data_quality_tests.py in render_html(self, obj)
    822             raise ValueError("column_name should be present")
    823 
--> 824         counts_data = obj.metric.get_result().plot_data.counts_of_values
    825         if counts_data is not None:
    826             curr_df = counts_data["current"]

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/metrics/base_metric.py in get_result(self)
     51         result = self.context.metric_results.get(self, None)
     52         if isinstance(result, ErrorResult):
---> 53             raise result.exception
     54         if result is None:
     55             raise ValueError(f"No result found for metric {self} of type {type(self).__name__}")

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/suite/base_suite.py in run_checks(self)
    260             try:
    261                 logging.debug(f"Executing {type(test)}...")
--> 262                 test_results[test] = test.check()
    263             except BaseException as ex:
    264                 test_results[test] = TestResult(

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/tests/data_quality_tests.py in check(self)
    443         #     return result
    444 
--> 445         result = super().check()
    446 
    447         if self.value is None:

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/tests/base_test.py in check(self)
    302             status=TestResult.SKIPPED,
    303         )
--> 304         value = self.calculate_value_for_test()
    305         self.value = value
    306         result.description = self.get_description(value)

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/tests/data_quality_tests.py in calculate_value_for_test(self)
    786 
    787     def calculate_value_for_test(self) -> Optional[Numeric]:
--> 788         features_stats = self.metric.get_result().current_characteristics
    789         most_common_percentage = features_stats.most_common_percentage
    790 

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/metrics/base_metric.py in get_result(self)
     51         result = self.context.metric_results.get(self, None)
     52         if isinstance(result, ErrorResult):
---> 53             raise result.exception
     54         if result is None:
     55             raise ValueError(f"No result found for metric {self} of type {type(self).__name__}")

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/suite/base_suite.py in run_calculate(self, data)
    242                     logging.debug(f"Executing {type(calculation)}...")
    243                     try:
--> 244                         calculations[calculation] = calculation.calculate(data)
    245                     except BaseException as ex:
    246                         calculations[calculation] = ErrorResult(ex)

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/metrics/data_integrity/column_summary_metric.py in calculate(self, data)
    192         if data.reference_data is not None:
    193             reference_data = data.reference_data
--> 194             ref_characteristics = self.map_data(get_features_stats(data.reference_data[self.column_name], column_type))
    195         curr_characteristics = self.map_data(get_features_stats(data.current_data[self.column_name], column_type))
    196 

~/anaconda3/envs/python3/lib/python3.8/site-packages/evidently/calculations/data_quality.py in get_features_stats(feature, feature_type)
    186         # round most common feature value for numeric features to 1e-5
    187         if not np.issubdtype(feature, np.number):
--> 188             feature = feature.astype(float)
    189         result.most_common_value = np.round(result.most_common_value, 5)
    190         result.infinite_count = int(np.sum(np.isinf(feature)))

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/generic.py in astype(self, dtype, copy, errors)
   5813         else:
   5814             # else, only a single dtype is given
-> 5815             new_data = self._mgr.astype(dtype=dtype, copy=copy, errors=errors)
   5816             return self._constructor(new_data).__finalize__(self, method="astype")
   5817 

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/internals/managers.py in astype(self, dtype, copy, errors)
    416 
    417     def astype(self: T, dtype, copy: bool = False, errors: str = "raise") -> T:
--> 418         return self.apply("astype", dtype=dtype, copy=copy, errors=errors)
    419 
    420     def convert(

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/internals/managers.py in apply(self, f, align_keys, ignore_failures, **kwargs)
    325                     applied = b.apply(f, **kwargs)
    326                 else:
--> 327                     applied = getattr(b, f)(**kwargs)
    328             except (TypeError, NotImplementedError):
    329                 if not ignore_failures:

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/internals/blocks.py in astype(self, dtype, copy, errors)
    589         values = self.values
    590 
--> 591         new_values = astype_array_safe(values, dtype, copy=copy, errors=errors)
    592 
    593         new_values = maybe_coerce_values(new_values)

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/dtypes/cast.py in astype_array_safe(values, dtype, copy, errors)
   1307 
   1308     try:
-> 1309         new_values = astype_array(values, dtype, copy=copy)
   1310     except (ValueError, TypeError):
   1311         # e.g. astype_nansafe can fail on object-dtype of strings

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/dtypes/cast.py in astype_array(values, dtype, copy)
   1255 
   1256     else:
-> 1257         values = astype_nansafe(values, dtype, copy=copy)
   1258 
   1259     # in pandas we don't store numpy str dtypes, so convert to object

~/anaconda3/envs/python3/lib/python3.8/site-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy, skipna)
   1199     if copy or is_object_dtype(arr.dtype) or is_object_dtype(dtype):
   1200         # Explicit copy, or required since NumPy can't view from / to object.
-> 1201         return arr.astype(dtype, copy=True)
   1202 
   1203     return arr.astype(dtype, copy=copy)

ValueError: could not convert string to float: 'Canteen'

Expected behavior: To see the Data Quality report

To Reproduce: After Evidently imports,

data_quality = TestSuite(tests=[
    DataQualityTestPreset(),
])

data_quality.run(reference_data=reference_df, current_data=current_df)
data_quality

System: AWS SageMaker with Python 3.8.12 and Evidently 0.2.0

[emeli-dral]

@AbhiPawar5 Cool, good to know! We continue to improve automatic input data parsing process. I hope we will do better soon 😃

[AbhiPawar5]

Hi @emeli-dral and @elenasamuylova, using ColumnMapping solved this issue 😃 Please feel free to close this issue.

Thanks for your help.