Update app.py

app.py

@@ -189,7 +189,10 @@ if uploaded_file is not None:
             char_bigrams[bigram] += 1
     
     char_bigram_df = pd.DataFrame([
-        {'Bigram': ''.join(bigram), 'Char1': bigram[0], 'Char2': bigram[1], 'Count': count}
+        {'Bigram': ''.join(str(c) for c in bigram), 
+         'Char1': str(bigram[0]), 
+         'Char2': str(bigram[1]), 
+         'Count': int(count)}
         for bigram, count in char_bigrams.most_common(30)
     ])
     st.dataframe(char_bigram_df)
@@ -205,7 +208,7 @@ if uploaded_file is not None:
             char_trigrams[trigram] += 1
     
     char_trigram_df = pd.DataFrame([
-        {'Trigram': ''.join(trigram), 'Count': count}
+        {'Trigram': ''.join(str(c) for c in trigram), 'Count': int(count)}
         for trigram, count in char_trigrams.most_common(30)
     ])
     st.dataframe(char_trigram_df)
@@ -218,7 +221,7 @@ if uploaded_file is not None:
         word_bigrams[bigram] += 1
             
     word_bigram_df = pd.DataFrame([
-        {'Word1': bigram[0], 'Word2': bigram[1], 'Count': count}
+        {'Word1': str(bigram[0]), 'Word2': str(bigram[1]), 'Count': int(count)}
         for bigram, count in word_bigrams.most_common(20)
     ])
     st.dataframe(word_bigram_df)
@@ -231,7 +234,10 @@ if uploaded_file is not None:
         word_trigrams[trigram] += 1
             
     word_trigram_df = pd.DataFrame([
-        {'Word1': trigram[0], 'Word2': trigram[1], 'Word3': trigram[2], 'Count': count}
+        {'Word1': str(trigram[0]), 
+         'Word2': str(trigram[1]), 
+         'Word3': str(trigram[2]), 
+         'Count': int(count)}
         for trigram, count in word_trigrams.most_common(20)
     ])
     st.dataframe(word_trigram_df)
@@ -492,7 +498,9 @@ if uploaded_file is not None:
             ngrams[ngram] += 1
     
     ngram_df = pd.DataFrame([
-        {'Pattern': ''.join(ngram), 'Count': count, 'Percentage': f"{count/len(chars_list)*100:.2f}%"}
+        {'Pattern': ''.join(str(c) for c in ngram), 
+         'Count': int(count), 
+         'Percentage': f"{count/len(chars_list)*100:.2f}%"}
         for ngram, count in ngrams.most_common(30)
     ])
     st.dataframe(ngram_df)