add streamlit_piechart

streamlit_piechart

@@ -0,0 +1,74 @@
+import streamlit as st
+import pandas as pd
+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
+
+def analyze_sentiment(text):
+    polarity = TextBlob(str(text)).sentiment.polarity
+    if polarity >= 0.6:
+        return "Very Positive"
+    elif polarity >= 0.2:
+        return "Positive"
+    elif polarity > -0.2:
+        return "Neutral"
+    elif polarity > -0.6:
+        return "Negative"
+    else:
+        return "Very Negative"
+
+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"])
+
+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())
+        
+        # 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'.")
+        
+        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.")
+else:
+    st.write("Please upload an Excel file to get started.")