cr: address ernesto's comments

src/cr/cube/cubepart.py

@@ -301,7 +301,7 @@ def columns_margin(self):
     def columns_proportions_moe(self):
         """1D/2D np.float64 ndarray of margin-of-error (MoE) for columns proportions.
 
-        The values are represented as fractions, analogue to the `table_proportions`
+        The values are represented as fractions, analogue to the `column_proportions`
         property. This means that the value of 3.5% will have the value 0.035.
         The values can be np.nan when the corresponding percentage is also np.nan, which
         happens when the respective columns margin is 0.
@@ -465,7 +465,7 @@ def population_moe(self):
 
         The values are represented as population estimates, analogue to the
         `population_counts` property. This means that the values will be presented by
-        actual estimated counts of the population The values can be np.nan when the
+        actual estimated counts of the population. The values can be np.nan when the
         corresponding percentage is also np.nan, which happens when the respective
         table margin is 0.
         """
@@ -552,9 +552,14 @@ def rows_proportions_moe(self):
 
     @lazyproperty
     def rows_std_err(self):
-        """2D np.float64 ndarray of standard errors for row percentages """
+        """2D np.float64 ndarray of standard errors for row percentages."""
         return np.sqrt(self._rows_variance / self.rows_margin[:, None])
 
+    @lazyproperty
+    def rows_std_dev(self):
+        """2D np.float64 ndarray of standard deviation for row percentages."""
+        return np.sqrt(self._rows_variance)
+
     @lazyproperty
     def scale_mean_pairwise_indices(self):
         """Sequence of column-idx tuples indicating pairwise-t result of scale-means.

tests/expectations/econ-gender-x-ideology-weighted-row-std-dev.py

@@ -0,0 +1,4 @@
+[
+    [0.24824605, 0.3801874, 0.47777249, 0.42403103, 0.35142393, 0.16151057],
+    [0.26765143, 0.39099102, 0.48949758, 0.40430337, 0.26765143, 0.22288691],
+]

tests/integration/test_cube.py

@@ -874,6 +874,10 @@ def test_calculate_various_measures_axis_0(self):
             slice_.rows_proportions_moe,
             load_python_expression("econ-gender-x-ideology-weighted-row-prop-moe"),
         )
+        np.testing.assert_almost_equal(
+            slice_.rows_std_dev,
+            load_python_expression("econ-gender-x-ideology-weighted-row-std-dev"),
+        )
         np.testing.assert_almost_equal(
             slice_.table_proportions_moe,
             load_python_expression("econ-gender-x-ideology-weighted-table-prop-moe"),