Update app.py

app.py

@@ -17,8 +17,12 @@ class pytrendsExpander:
         kw_list = [self.keyword]
         pytrends.build_payload(kw_list, cat=0, timeframe='today 1-m', geo='US', gprop='')
         queries = pytrends.related_queries()
-        df_results = pd.DataFrame(queries.get(self.keyword).get('top').rename_axis('ranking').reset_index())
-        return df_results.head(m)
+        
+        if self.keyword in queries and queries[self.keyword] is not None:
+            top_queries = queries[self.keyword].get('top')
+            if top_queries is not None and not top_queries.empty:
+                df_results = top_queries.rename_axis('ranking').reset_index()
+                return df_results.head(m)
 
 pytrends = TrendReq(hl='en-US', tz=360)
 
@@ -94,16 +98,20 @@ if kw_list:
             st.write(f"Related to '{keyword}':")
             expander = pytrendsExpander(keyword)
             related_df = expander.expand_search(10)
-            st.write(related_df)
             
-            # Generate and display word cloud
-            wordcloud = WordCloud(width=800, height=400, background_color='white').generate_from_frequencies(
-                dict(zip(related_df['query'], related_df['value']))
-            )
-            fig, ax = plt.subplots(figsize=(10, 5))
-            ax.imshow(wordcloud, interpolation='bilinear')
-            ax.axis('off')
-            st.pyplot(fig)
+            if not related_df.empty:
+                st.write(related_df)
+            
+            # Generate and display word cloud only if we have data
+                wordcloud = WordCloud(width=800, height=400, background_color='white').generate_from_frequencies(
+                    dict(zip(related_df['query'], related_df['value']))
+                )
+                fig, ax = plt.subplots(figsize=(10, 5))
+                ax.imshow(wordcloud, interpolation='bilinear')
+                ax.axis('off')
+                st.pyplot(fig)
+            else:
+                st.write(f"No related queries found for '{keyword}'.")
         
         st.subheader('Geographical Interest')
         interest_by_region = pytrends.interest_by_region(resolution='COUNTRY', inc_low_vol=True, inc_geo_code=True)