Bug fix for float precision calculation using categorical data with t…

…railing zeros. (capitalone#1125)
JGSweets · Jun 5, 2024 · 4491b97 · 4491b97
1 parent af9f275
commit 4491b97
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Showing 2 changed files with 11 additions and 1 deletion.
diff --git a/dataprofiler/profilers/float_column_profile.py b/dataprofiler/profilers/float_column_profile.py
@@ -305,7 +305,10 @@ def _get_float_precision(
 
         # length of sampled cells after all punctuation removed
         len_per_float = (
-            df_series_clean.sample(sample_size).replace(to_replace=r, value="").map(len)
+            df_series_clean.sample(sample_size)
+            .astype(object)
+            .replace(to_replace=r, value="")
+            .map(len)
         ).astype(float)
 
         # Determine statistics precision

diff --git a/dataprofiler/tests/profilers/test_float_column_profile.py b/dataprofiler/tests/profilers/test_float_column_profile.py
@@ -211,6 +211,13 @@ def test_profiled_precision(self):
                 msg=f"Errored for: {sample[0]}",
             )
 
+        # Validate categorical series with trailing zeros supported
+        categorical_series = pd.Series(
+            [202209, 202210, 202211], dtype="category"
+        ).apply(str)
+        float_profiler = FloatColumn("Name")
+        float_profiler.update(categorical_series)
+
     def test_profiled_min(self):
         # test with multiple values
         data = np.linspace(-5, 5, 11)