diff --git a/features/communication.py b/features/communication.py
index 209eabd..d92bd29 100644
--- a/features/communication.py
+++ b/features/communication.py
@@ -166,7 +166,7 @@ def count_comms(comm_df: pd.DataFrame, group_by=None) -> pd.DataFrame:
         data_type = "calls"
         comm_counts = (
             comm_df.value_counts(subset=group_by + ["participant_id", "call_type"])
-            .unstack()
+            .unstack(level="call_type", fill_value=0)
             .rename(columns=call_types)
             .add_prefix("no_")
         )
@@ -181,7 +181,7 @@ def count_comms(comm_df: pd.DataFrame, group_by=None) -> pd.DataFrame:
         comm_duration_total = (
             comm_df.groupby(group_by + ["participant_id", "call_type"])
             .sum()["call_duration"]
-            .unstack()
+            .unstack(level="call_type", fill_value=0)
             .rename(columns=call_types)
             .add_prefix("duration_total_")
         )
@@ -189,7 +189,7 @@ def count_comms(comm_df: pd.DataFrame, group_by=None) -> pd.DataFrame:
         comm_duration_max = (
             comm_df.groupby(group_by + ["participant_id", "call_type"])
             .max()["call_duration"]
-            .unstack()
+            .unstack(level="call_type", fill_value=0)
             .rename(columns=call_types)
             .add_prefix("duration_max_")
         )
@@ -208,7 +208,7 @@ def count_comms(comm_df: pd.DataFrame, group_by=None) -> pd.DataFrame:
         data_type = "sms"
         comm_counts = (
             comm_df.value_counts(subset=group_by + ["participant_id", "message_type"])
-            .unstack()
+            .unstack(level="message_type", fill_value=0)
             .rename(columns=sms_types)
             .add_prefix("no_")
         )
@@ -311,24 +311,34 @@ def calls_sms_features(
         group_by = []
     count_calls = count_comms(df_calls, group_by)
     count_sms = count_comms(df_sms, group_by)
-    count_joined = count_calls.merge(
-        count_sms, how="outer", left_index=True, right_index=True, validate="one_to_one"
-    ).assign(
-        proportion_calls_all=(
-            lambda x: x.no_calls_all / (x.no_calls_all + x.no_sms_all)
-        ),
-        proportion_calls_incoming=(
-            lambda x: x.no_incoming / (x.no_incoming + x.no_received)
-        ),
-        proportion_calls_missed_sms_received=(
-            lambda x: x.no_missed / (x.no_missed + x.no_received)
-        ),
-        proportion_calls_outgoing=(
-            lambda x: x.no_outgoing / (x.no_outgoing + x.no_sent)
-        ),
-        proportion_calls_contacts=(
-            lambda x: x.no_contacts_calls / (x.no_contacts_calls + x.no_contacts_sms)
+    count_joined = (
+        count_calls.merge(
+            count_sms,
+            how="outer",
+            left_index=True,
+            right_index=True,
+            validate="one_to_one",
         )
-        # Calculate new features and create additional columns
+        .fillna(0, downcast="infer")
+        .assign(
+            proportion_calls_all=(
+                lambda x: x.no_calls_all / (x.no_calls_all + x.no_sms_all)
+            ),
+            proportion_calls_incoming=(
+                lambda x: x.no_incoming / (x.no_incoming + x.no_received)
+            ),
+            proportion_calls_missed_sms_received=(
+                lambda x: x.no_missed / (x.no_missed + x.no_received)
+            ),
+            proportion_calls_outgoing=(
+                lambda x: x.no_outgoing / (x.no_outgoing + x.no_sent)
+            ),
+            proportion_calls_contacts=(
+                lambda x: x.no_contacts_calls
+                / (x.no_contacts_calls + x.no_contacts_sms)
+            )
+            # Calculate new features and create additional columns
+        )
+        .fillna(0.5, downcast="infer")
     )
     return count_joined