diff --git a/TM1py/Utils/Utils.py b/TM1py/Utils/Utils.py
index a8a5a527..f0015ee3 100644
--- a/TM1py/Utils/Utils.py
+++ b/TM1py/Utils/Utils.py
@@ -548,12 +548,12 @@ def build_dataframe_from_csv(raw_csv, sep='~', shaped: bool = False,
     if 'dtype' not in kwargs:
         kwargs['dtype'] = {'Value': None, **{col: str for col in range(999)}}
     try:
-        df = pd.read_csv(StringIO(raw_csv), sep=sep, na_values=["", None], keep_default_na=False, **kwargs)
+        df = pd.read_csv(StringIO(raw_csv), sep=sep, na_values=[], keep_default_na=False, **kwargs)
 
     except ValueError:
         # retry with dtype 'str' for results with a mixed value column
         kwargs['dtype'] = {'Value': str, **{col: str for col in range(999)}}
-        df = pd.read_csv(StringIO(raw_csv), sep=sep, na_values=["", None], keep_default_na=False, **kwargs)
+        df = pd.read_csv(StringIO(raw_csv), sep=sep, na_values=[], keep_default_na=False, **kwargs)
 
     if fillna_numeric_attributes:
         fill_numeric_bool_list = [attr_type.lower() == 'numeric' for dimension, attributes in
@@ -562,7 +562,7 @@ def build_dataframe_from_csv(raw_csv, sep='~', shaped: bool = False,
         fill_numeric_bool_list += [False]  # for the value column
         df = df.apply(
             lambda col:
-            col.fillna(fillna_numeric_attributes_value) if fill_numeric_bool_list[
+            col.replace(['', 'None'], np.nan).fillna(fillna_numeric_attributes_value) if fill_numeric_bool_list[
                 list(df.columns.values).index(col.name)] else col,
             axis=0)
 
@@ -573,10 +573,13 @@ def build_dataframe_from_csv(raw_csv, sep='~', shaped: bool = False,
         fill_string_bool_list += [False]  # for the value column
         df = df.apply(
             lambda col:
-            col.fillna(fillna_string_attributes_value) if fill_string_bool_list[
+            col.replace(['', 'None'], np.nan).fillna(fillna_string_attributes_value) if fill_string_bool_list[
                 list(df.columns.values).index(col.name)] else col,
             axis=0)
 
+    if 'Value' in df.columns:
+        df['Value'] = df['Value'].replace(['', 'None'], np.nan)
+
     if not shaped:
         return df
 
diff --git a/Tests/Utils_test.py b/Tests/Utils_test.py
index 77c63d2d..6a6144c1 100644
--- a/Tests/Utils_test.py
+++ b/Tests/Utils_test.py
@@ -2,6 +2,7 @@
 import unittest
 from pathlib import Path
 
+import numpy as np
 from TM1py.Services import TM1Service
 from TM1py.Utils import (
     Utils,
@@ -9,7 +10,7 @@
     integerize_version,
     verify_version, get_cube, resembles_mdx, format_url, add_url_parameters, extract_cell_updateable_property,
     CellUpdateableProperty, cell_is_updateable, extract_cell_properties_from_odata_context,
-    map_cell_properties_to_compact_json_response, frame_to_significant_digits, drop_dimension_properties
+    map_cell_properties_to_compact_json_response, frame_to_significant_digits, drop_dimension_properties, build_dataframe_from_csv
 )
 
 from .Utils import skip_if_deprecated_in_version
@@ -103,6 +104,12 @@ def test_get_dimensions_from_where_clause_happy_case(self):
         dimensions = get_dimensions_from_where_clause(mdx)
         self.assertEqual(["DIM2", "DIM1"], dimensions)
 
+    def test_build_dataframe_from_csv(self):
+        raw_csv = """Dim A~Dim B~Dim C~Dim D~Dim E~Dim F~Value\r\nN5~N5~N1~N5~N5~N1~1\r\nN5~N5~N1~N5~N5~N2~1\r\nN5~N5~N1~N5~N5~N5~1\r\nN5~N5~N1~N5~N5~S1~1\r\nN5~N5~N1~N5~N5~C1~1\r\nNone~N5~N1~N5~N5~N1~1\r\nNone~N5~N1~N5~N5~N2~1\r\nNone~N5~N1~N5~N5~N5~None\r\nNone~N5~N1~N5~N5~S1~1\r\nNone~N5~N1~N5~N5~C1~1"""
+        test_result = build_dataframe_from_csv(raw_csv)
+        result = {'Dim A': {0: 'N5', 1: 'N5', 2: 'N5', 3: 'N5', 4: 'N5', 5: 'None', 6: 'None', 7: 'None', 8: 'None', 9: 'None'}, 'Dim B': {0: 'N5', 1: 'N5', 2: 'N5', 3: 'N5', 4: 'N5', 5: 'N5', 6: 'N5', 7: 'N5', 8: 'N5', 9: 'N5'}, 'Dim C': {0: 'N1', 1: 'N1', 2: 'N1', 3: 'N1', 4: 'N1', 5: 'N1', 6: 'N1', 7: 'N1', 8: 'N1', 9: 'N1'}, 'Dim D': {0: 'N5', 1: 'N5', 2: 'N5', 3: 'N5', 4: 'N5', 5: 'N5', 6: 'N5', 7: 'N5', 8: 'N5', 9: 'N5'}, 'Dim E': {0: 'N5', 1: 'N5', 2: 'N5', 3: 'N5', 4: 'N5', 5: 'N5', 6: 'N5', 7: 'N5', 8: 'N5', 9: 'N5'}, 'Dim F': {0: 'N1', 1: 'N2', 2: 'N5', 3: 'S1', 4: 'C1', 5: 'N1', 6: 'N2', 7: 'N5', 8: 'S1', 9: 'C1'}, 'Value': {0: '1', 1: '1', 2: '1', 3: '1', 4: '1', 5: '1', 6: '1', 7: np.nan, 8: '1', 9: '1'}}
+        self.assertEqual(result, test_result.to_dict())
+
     def test_get_dimensions_from_where_clause_no_where(self):
         mdx = """
         SELECT {[dim3].[e2]} ON COLUMNS, {[dim4].[e5]} ON ROWS FROM [cube]