Minor refactor of z-score to use the correct standard deviation

qf_lib/common/utils/miscellaneous/z_score_outliers_cut.py

@@ -13,25 +13,17 @@
 #     limitations under the License.
 
 from numpy import log
-from qf_lib.common.utils.numberutils.is_finite_number import is_finite_number
 from qf_lib.containers.series.qf_series import QFSeries
 
 
 def z_score_outliers_cut(series: QFSeries) -> QFSeries:
     """ Compute z-score for a series with logarithm the series and cutting std above 2 and -2 """
-    is_valid = series.map(is_finite_number)
-
     # take a log to remove the outliers, then calculate z_score
-    clean_series = series[is_valid]
-    shift_value = 1 - clean_series.min()
-    log_series = log(clean_series.values.astype(float) + shift_value)
+    shift_value = 1 - series.min()
+    log_series = log(series.astype(float) + shift_value)
     result = (log_series - log_series.mean()) / log_series.std()
 
     # constraint the limits at +-2
     result = result.clip(-2, 2)
-
-    # for unknown or invalid values use 0
-    final = QFSeries(index=series.index)
-    final[is_valid] = result
-    final[~is_valid] = 0
-    return final
+    result = result.fillna(0.0)
+    return result