modified in app

app.py

@@ -4,14 +4,8 @@ import matplotlib.pyplot as plt
 from textblob import TextBlob
 
 def load_data(uploaded_file):
-    # Load Excel file, supports both .xlsx and .xls
-    try:
-        df = pd.read_excel(uploaded_file)  # Automatically detects file format
-        df.columns = df.columns.str.strip().str.lower()  # Normalize column names
-        return df
-    except Exception as e:
-        st.error(f"Error loading file: {e}")
-        return None
+    df = pd.read_excel(uploaded_file)
+    return df
 
 def analyze_sentiment(text):
     polarity = TextBlob(str(text)).sentiment.polarity
@@ -28,47 +22,29 @@ def analyze_sentiment(text):
 
 st.title("Sentiment Analysis with Pie Chart")
 
-# File uploader supports .xlsx and .xls
-uploaded_file = st.file_uploader("Upload an Excel file with text data", type=["xlsx", "xls"])
+uploaded_file = st.file_uploader("Upload an Excel file with text data", type=["xlsx"])
 
 if uploaded_file is not None:
     df = load_data(uploaded_file)
-    if df is not None:
-        st.write("Columns in your file:", df.columns.tolist())
+    if "text" not in df.columns:
+        st.error("Error: The file must contain a 'text' column.")
+    else:
+        df["Sentiment"] = df["text"].apply(analyze_sentiment)
         
-        # Allow the user to select a column if 'text' is not already present
-        if "text" not in df.columns:
-            selected_column = st.selectbox("Select the column to use as text data:", df.columns)
-            if st.button("Confirm Selection"):
-                df.rename(columns={selected_column: "text"}, inplace=True)
-                st.success(f"Column '{selected_column}' renamed to 'text'.")
+        st.write("Here is a preview of the data:")
+        st.write(df.head())
         
-        if "text" in df.columns:  # Check again if 'text' column is present after renaming
-            df["Sentiment"] = df["text"].apply(analyze_sentiment)
-            
-            st.write("Here is a preview of the data:")
-            st.write(df.head())
-            
-            sentiment_counts = df["Sentiment"].value_counts()
-            
-            fig, ax = plt.subplots()
-            ax.pie(sentiment_counts, labels=sentiment_counts.index, autopct="%1.1f%%", colors=["green", "lightgreen", "gray", "orange", "red"])
-            ax.set_title("Sentiment Distribution")
-            st.pyplot(fig)
-            
-            # Export processed data to Excel file (.xlsx) without explicitly using xlsxwriter
-            output_file = "sentiment_results.xlsx"
-            df.to_excel(output_file, index=False, sheet_name="Sentiment Analysis")
-
-            # Download button for Excel file
-            with open(output_file, "rb") as f:
-                st.download_button(
-                    "Download Sentiment Data (Excel)",
-                    f,
-                    "sentiment_results.xlsx",
-                    "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
-                )
-        else:
-            st.warning("Please select a column to rename as 'text' and proceed.")
+        sentiment_counts = df["Sentiment"].value_counts()
+        
+        fig, ax = plt.subplots()
+        ax.pie(sentiment_counts, labels=sentiment_counts.index, autopct="%1.1f%%", colors=["green", "lightgreen", "gray", "orange", "red"])
+        ax.set_title("Sentiment Distribution")
+        st.pyplot(fig)
+        
+        csv = df.to_csv(index=False)
+        st.download_button("Download Sentiment Data", csv, "sentiment_results.csv", "text/csv")
 else:
-    st.write("Please upload an Excel file to get started.")
+    st.write("Please upload an Excel file to get started.")
+
+
+