diff --git a/src/main_generator_notebook.ipynb b/src/main_generator_notebook.ipynb
index 42c20fd..f32bbe8 100644
--- a/src/main_generator_notebook.ipynb
+++ b/src/main_generator_notebook.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -48,7 +48,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 20,
    "metadata": {
     "scrolled": false
    },
@@ -56,7 +56,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3b95936354a245759c69cd0157ff7791",
+       "model_id": "c669d7f3d67143ba988ff8ea2b9a9034",
        "version_major": 2,
        "version_minor": 0
       },
@@ -70,7 +70,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6e14e93ab57c4fb784c6d42cd58bbfc2",
+       "model_id": "339f144c68394d0d9499b718b09f4faa",
        "version_major": 2,
        "version_minor": 0
       },
@@ -84,7 +84,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "25c5c668597341fab5b2b99c3580d516",
+       "model_id": "90a6132e8a5f44b7a71a397cab84267b",
        "version_major": 2,
        "version_minor": 0
       },
@@ -98,7 +98,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "ba12d221cef04e2cbabf48cd81d6ee6a",
+       "model_id": "1f638ca7da764cb09cac8e40a99c13a6",
        "version_major": 2,
        "version_minor": 0
       },
diff --git a/src/synthetic_data_generation/generators.py b/src/synthetic_data_generation/generators.py
index a7591f6..62703c1 100644
--- a/src/synthetic_data_generation/generators.py
+++ b/src/synthetic_data_generation/generators.py
@@ -1314,18 +1314,30 @@ def create_a_summary_table(df_total_user: pd.DataFrame,
                     places_count = 0.0
                     delta_count = 0.0
                     if not temp_df.empty:
-                        social_situation_count = temp_df[f"{meal}_social_situation"].value_counts(
+                        filter_nan_out = temp_df[~temp_df[f"{meal}_social_situation"].isin([
+                                                                                           'N/A'])]
+                        social_situation_count = filter_nan_out[f"{meal}_social_situation"].value_counts(
+                        )
+                        filter_nan_out = temp_df[~temp_df[f"{meal}_place"].isin([
+                                                                                'N/A'])]
+                        places_count = filter_nan_out[f"{meal}_place"].value_counts(
                         )
-                        places_count = temp_df[f"{meal}_place"].value_counts()
                         delta_count = {
                             "mean": temp_df[f"{meal}_delta"].mean(),
                             "std": temp_df[f"{meal}_delta"].std()
                         }
-                        temp_list.append(f"""<li><strong>{meal.capitalize()}:</strong>
-                                        <p>social situations consume meal: {', '.join([ind+':'+str(social_situation_count[ind]) if ind != "N/A" else "N/A" for ind in social_situation_count.index])}</p> 
-                                        <p>places consume meal: {', '.join([ind+':'+str(places_count[ind]) if ind != "N/A" else "N/A" for ind in places_count.index])}</p>
-                                        <p>appreciation: {delta_count['mean']} &plusmn; {delta_count['std']}</p>
+                        if len(places_count) == 0 and len(social_situation_count) == 0:
+                            temp_list.append(f"""<li><strong>{meal.capitalize()}:</strong>
+                                        <p>social situations consume meal: N/A</p> 
+                                        <p>places consume meal: N/A</p>
+                                        <p>appreciation: N/A</p>
                                         </li>""")
+                        else:
+                            temp_list.append(f"""<li><strong>{meal.capitalize()}:</strong>
+                                            <p>social situations consume meal: {', '.join([ind+':'+str(social_situation_count[ind]) if ind != "N/A" else "N/A" for ind in social_situation_count.index])}</p> 
+                                            <p>places consume meal: {', '.join([ind+':'+str(places_count[ind]) if ind != "N/A" else "N/A" for ind in places_count.index])}</p>
+                                            <p>appreciation: {delta_count['mean']} &plusmn; {delta_count['std']}</p>
+                                            </li>""")
                         # print(
                         # f"calculated values condition {condition}: {meal} mean {mean} std {std}")
                     else: