Top Profiler Structured Diff

dataprofiler/profilers/profile_builder.py

@@ -196,6 +196,69 @@ def __add__(self, other):
             )
         return merged_profile
 
+    def diff(self, other_profile, options=None):
+        """
+        Finds the difference between 2 StructuredCols and returns the report
+
+        :param other: Structured col finding the difference with this one.
+        :type other: StructuredColProfiler
+        :param options: options to change results of the difference
+        :type options: dict
+        :return: difference of the structured column
+        :rtype: dict
+        """
+        unordered_profile = dict()
+        for key, profile in self.profiles.items():
+            if key in other_profile.profiles:
+                comp_diff = self.profiles[key].diff(other_profile.profiles[key],
+                                                    options=options)
+                utils.dict_merge(unordered_profile, comp_diff)
+
+        name = self.name
+        if isinstance(self.name, np.integer):
+            name = int(name)
+
+        unordered_profile.update({
+            "column_name": name,
+        })
+
+        unordered_profile["statistics"].update({
+            "sample_size": utils.find_diff_of_numbers(
+                self.sample_size, other_profile.sample_size),
+            "null_count": utils.find_diff_of_numbers(
+                self.null_count, other_profile.null_count),
+            "null_types": utils.find_diff_of_lists_and_sets(
+                self.null_types, other_profile.null_types),
+            "null_types_index": utils.find_diff_of_dicts_with_diff_keys(
+                self.null_types_index, other_profile.null_types_index),
+        })
+
+        if unordered_profile.get("data_type", None) is not None:
+            unordered_profile["statistics"].update({
+                "data_type_representation":
+                    unordered_profile["data_type_representation"]
+            })
+
+        dict_order = [
+            "column_name",
+            "data_type",
+            "data_label",
+            "categorical",
+            "order",
+            "statistics",
+        ]
+        profile = OrderedDict()
+        if 'data_label_profile' not in self.profiles or\
+                'data_label_profile' not in other_profile.profiles:
+            dict_order.remove("data_label")
+        for key in dict_order:
+            try:
+                profile[key] = unordered_profile[key]
+            except KeyError as e:
+                profile[key] = None
+
+        return profile
+
     @property
     def profile(self):
         unordered_profile = dict()
@@ -556,6 +619,30 @@ def __add__(self, other):
 
         return merged_profile
 
+    def diff(self, other_profile, options=None):
+        """
+        Finds the difference of two profiles
+
+        :param other: profile being added to this one.
+        :type other: BaseProfiler
+        :return: diff of the two profiles
+        :rtype: dict
+        """
+        if type(other_profile) is not type(self):
+            raise TypeError('`{}` and `{}` are not of the same profiler type.'.
+                            format(type(self).__name__, 
+                                   type(other_profile).__name__))
+
+        diff_profile = OrderedDict([
+            ("global_stats", {
+                "file_type": utils.find_diff_of_strings_and_bools(
+                    self.file_type, other_profile.file_type),
+                "encoding": utils.find_diff_of_strings_and_bools(
+                    self.encoding, other_profile.encoding),
+            })])
+
+        return diff_profile
+
     def _get_sample_size(self, data):
         """
         Determines the minimum sampling size for profiling the dataset.
@@ -1241,6 +1328,67 @@ def __add__(self, other):
 
         return merged_profile
 
+    def diff(self, other_profile, options=None):
+        """
+        Finds the difference between 2 Profiles and returns the report
+
+        :param other: profile finding the difference with this one
+        :type other: StructuredProfiler
+        :param options: options to change results of the difference
+        :type options: dict
+        :return: difference of the profiles
+        :rtype: dict
+        """
+        report = super().diff( other_profile, options)
+        report["global_stats"].update({
+                "samples_used": utils.find_diff_of_numbers(
+                    self._max_col_samples_used, 
+                    other_profile._max_col_samples_used),
+                "column_count": utils.find_diff_of_numbers(
+                    len(self._profile), len(other_profile._profile)),
+                "row_count": utils.find_diff_of_numbers(
+                    self.total_samples, other_profile.total_samples),
+                "row_has_null_ratio": utils.find_diff_of_numbers(
+                    self._get_row_has_null_ratio(), 
+                    other_profile._get_row_has_null_ratio()),
+                "row_is_null_ratio": utils.find_diff_of_numbers(
+                    self._get_row_is_null_ratio(),
+                    other_profile._get_row_is_null_ratio()),
+                "unique_row_ratio": utils.find_diff_of_numbers(
+                    self._get_unique_row_ratio(),
+                    other_profile._get_unique_row_ratio()),
+                "duplicate_row_count": utils.find_diff_of_numbers(
+                    self._get_duplicate_row_count(),
+                    other_profile._get_row_is_null_ratio()),
+                "correlation_matrix": utils.find_diff_of_matrices(
+                    self.correlation_matrix, 
+                    other_profile.correlation_matrix),
+                "profile_schema": defaultdict(list)})
+        report.update({"data_stats": []})
+
+        # Extract the schema of each profile
+        self_profile_schema = defaultdict(list)
+        other_profile_schema = defaultdict(list)
+        for i in range(len(self._profile)):
+            col_name = self._profile[i].name
+            self_profile_schema[col_name].append(i)
+        for i in range(len(other_profile._profile)):
+            col_name = other_profile._profile[i].name
+            other_profile_schema[col_name].append(i)
+
+        report["global_stats"]["profile_schema"] = \
+            utils.find_diff_of_dicts_with_diff_keys(self_profile_schema, 
+                                                    other_profile_schema)
+
+        # Only find the diff of columns if the schemas are exactly the same
+        if self_profile_schema == other_profile_schema:
+            for i in range(len(self._profile)):
+                report["data_stats"].append(
+                    self._profile[i].diff(other_profile._profile[i], 
+                                          options=options))
+
+        return _prepare_report(report)
+
     @property
     def _max_col_samples_used(self):
         """

dataprofiler/profilers/utils.py

@@ -493,6 +493,31 @@ def find_diff_of_dicts(dict1, dict2):
     return diff
 
 
+def find_diff_of_matrices(matrix1, matrix2):
+    """
+    Finds the difference between two matrices.
+
+    :param matrix1: the first matrix
+    :type matrix1: list(list(float))
+    :param matrix2: the second matrix
+    :type matrix2: list(list(float))
+    :return: Difference in the matrix
+    :rtype: list(list(float))
+    """
+
+    diff = None
+
+    if matrix1 is not None and matrix2 is not None:
+        mat1 = np.array(matrix1, dtype=np.float)
+        mat2 = np.array(matrix2, dtype=np.float)
+
+        if mat1.shape == mat2.shape:
+            diff = mat1 - mat2
+            if ((diff == 0) | np.isnan(diff)).all():
+                diff = "unchanged"
+
+    return diff
+
 def find_diff_of_dicts_with_diff_keys(dict1, dict2):
     """
     Finds the difference between two dicts. For each key in each dict,