msg

app.py

@@ -30,21 +30,24 @@ if uploaded_file is not None:
     st.sidebar.write("✅ File Uploaded Successfully!")
     
     text_column = st.sidebar.selectbox("Select Text Column", df.columns)
-    
+
     if st.sidebar.button("Analyze Sentiment"):
-        df["Sentiment"] = predict_sentiment(df[text_column].astype(str).tolist())
-        
-        # Display results
-        st.write("### Sentiment Analysis Results:")
-        st.dataframe(df[[text_column, "Sentiment"]])
-        
-        # Pie chart
-        sentiment_counts = df["Sentiment"].value_counts()
-        fig, ax = plt.subplots()
-        ax.pie(sentiment_counts, labels=sentiment_counts.index, autopct='%1.1f%%', colors=["red", "orange", "gray", "lightgreen", "green"])
-        ax.set_title("Sentiment Distribution")
-        st.pyplot(fig)
-        
-        # Download option
-        st.sidebar.download_button("Download Results", df.to_csv(index=False).encode('utf-8'), "sentiment_results.csv", "text/csv")
+        st.session_state.df = df  # Store dataframe in session state
+        st.session_state.df["Sentiment"] = predict_sentiment(df[text_column].astype(str).tolist())
+        st.session_state.analysis_done = True  # Set flag to indicate analysis is done
+
+# Check if analysis is done and persist results
+if "analysis_done" in st.session_state and st.session_state.analysis_done:
+    df = st.session_state.df  # Retrieve dataframe from session state
+    st.write("### Sentiment Analysis Results:")
+    st.dataframe(df[[text_column, "Sentiment"]])
+    
+    # Pie chart
+    sentiment_counts = df["Sentiment"].value_counts()
+    fig, ax = plt.subplots()
+    ax.pie(sentiment_counts, labels=sentiment_counts.index, autopct='%1.1f%%', colors=["red", "orange", "gray", "lightgreen", "green"])
+    ax.set_title("Sentiment Distribution")
+    st.pyplot(fig)
 
+    # Download button (chart remains visible)
+    st.sidebar.download_button("Download Results", df.to_csv(index=False).encode('utf-8'), "sentiment_results.csv", "text/csv")