diff --git a/data_bridges_knots/__init__.py b/data_bridges_knots/__init__.py
index 9d0deb0..7ea5fa6 100644
--- a/data_bridges_knots/__init__.py
+++ b/data_bridges_knots/__init__.py
@@ -5,6 +5,6 @@
 """
 
 from .client import DataBridgesShapes
-from .labels import get_column_labels, get_value_labels, map_value_labels
+from .helpers import get_column_labels, get_value_labels, map_value_labels
 
-__all__ = ['DataBridgesShapes', 'labels']
+__all__ = ['DataBridgesShapes', 'helpers']
diff --git a/data_bridges_knots/client.py b/data_bridges_knots/client.py
index a444eec..5bdc4d1 100644
--- a/data_bridges_knots/client.py
+++ b/data_bridges_knots/client.py
@@ -116,7 +116,10 @@ def get_household_survey(self, survey_id, access_type, page_size=600):
 
         df = pd.DataFrame(responses)
 
-        df.apply(lambda x: pd.to_numeric(x, errors='coerce', downcast='integer').fillna(9999).astype(np.int64 if x.dtype == 'int64' else x.dtype))
+        df = df.apply(lambda x: pd.to_numeric(x, errors='ignore', downcast='integer').fillna(9999).astype(int if x.dtype == 'int' or x.dtype == 'float' else x.dtype))
+
+        # df = df.apply(lambda x: pd.to_numeric(x, errors='ignore', downcast='integer').fillna(9999).astype(int if x.dtype == 'float' else x.dtype))
+
         df = df.replace({9999: None})
         return df
 
diff --git a/data_bridges_knots/labels.py b/data_bridges_knots/helpers.py
similarity index 80%
rename from data_bridges_knots/labels.py
rename to data_bridges_knots/helpers.py
index b6c21f0..e0b94ec 100644
--- a/data_bridges_knots/labels.py
+++ b/data_bridges_knots/helpers.py
@@ -11,9 +11,9 @@ def get_value_labels(df):
         name = row["name"]
         choice = row["choices"]
         if name in categories_dict:
-            categories_dict[name].update({int(choice["name"]): choice["label"]})
+            categories_dict[name].update({(choice["name"]): choice["label"]})
         else:
-            categories_dict[name] = {int(choice["name"]): choice["label"]}
+            categories_dict[name] = {(choice["name"]): choice["label"]}
     return categories_dict
 
 def get_column_labels(df):
@@ -42,9 +42,9 @@ def map_value_labels(survey_data, questionnaire):
         name = row["name"]
         choice = row["choices"]
         if name in categories_dict:
-            categories_dict[name].update({int(choice["name"]): choice["label"]})
+            categories_dict[name].update({(choice["name"]): choice["label"]})
         else:
-            categories_dict[name] = {int(choice["name"]): choice["label"]}
+            categories_dict[name] = {(choice["name"]): choice["label"]}
 
     # Map the categories to survey_data
     survey_data_value_labels = survey_data.copy()
@@ -55,3 +55,9 @@ def map_value_labels(survey_data, questionnaire):
 
     return survey_data_value_labels
 
+def as_numeric(df, cols = []):
+    for col in cols:
+        df[col].apply(lambda x: x.astype(int))
+    return df
+
+