diff --git a/setup.py b/setup.py
index 77ce7eb..e84e792 100644
--- a/setup.py
+++ b/setup.py
@@ -7,7 +7,7 @@
 
 setup(
     name='mdatagen',
-    version='0.1.61',
+    version='0.1.62',
     keywords=['machine learning', 'preprocessing data'],
     packages=find_packages(where="src"),
     package_dir={"": "src"},
diff --git a/src/mdatagen/multivariate/mMNAR.py b/src/mdatagen/multivariate/mMNAR.py
index 84f555f..0bcbabe 100644
--- a/src/mdatagen/multivariate/mMNAR.py
+++ b/src/mdatagen/multivariate/mMNAR.py
@@ -109,7 +109,7 @@ def random(self, missing_rate: int = 10, deterministic:bool = False):
             x_miss = np.random.choice(options_xmiss)
 
             if x_miss not in xmiss_multiva:
-                x_f = self.dataset.loc[:, x_miss].values
+                x_f = self.dataset.loc[:, x_miss]
 
                 if deterministic:
                     # Observed feature
@@ -184,7 +184,7 @@ def correlated(self, missing_rate: int = 10, deterministic:bool = False):
 
             N = round(len(self.dataset) * cutK)
 
-            x_f = self.dataset.loc[:, x_miss].values
+            x_f = self.dataset.loc[:, x_miss]
 
             if deterministic:
                 # Observed feature
@@ -267,9 +267,9 @@ def median(self, missing_rate: int = 10, deterministic:bool = False):
 
             choice = np.random.choice([0, 1])
             if choice == 0:
-                x_f = self.dataset.loc[g1_index, col].values
+                x_f = self.dataset.loc[g1_index, col]
             else:
-                x_f = self.dataset.loc[g2_index, col].values
+                x_f = self.dataset.loc[g2_index, col]
 
             if deterministic:
                 # Observed feature
diff --git a/src/mdatagen/univariate/uMNAR.py b/src/mdatagen/univariate/uMNAR.py
index b3bf144..e8fd271 100644
--- a/src/mdatagen/univariate/uMNAR.py
+++ b/src/mdatagen/univariate/uMNAR.py
@@ -91,7 +91,7 @@ def run(self, deterministic:bool = False):
 
         """
 
-        x_f = self.dataset.loc[:, self.x_miss].values
+        x_f = self.dataset.loc[:, self.x_miss]
 
         if deterministic:
             # Observed feature