import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt
from textblob import TextBlob

def load_data(uploaded_file):
    df = pd.read_excel(uploaded_file)
    return df

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")

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 "text" not in df.columns:
        st.error("Error: The file must contain a 'text' column.")
    else:
        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)
        
        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.")