import streamlit as st
import seaborn as sns
import matplotlib.pyplot as plt
import pandas as pd

# Load data
def load_data():
    df = pd.read_csv("processed_data.csv")  # replace with your dataset
    return df

# Create Streamlit app
def app():
    # Title for the app
    st.title("Pizza Sales Data Analysis Dashboard")
    df = load_data()

    df = pd.DataFrame(df)

    # Calculate key metrics
    total_orders = df['order_id'].nunique()
    total_revenue = df['total_price'].sum()
    most_popular_size = df['pizza_size'].value_counts().idxmax()
    most_frequent_category = df['pizza_category'].value_counts().idxmax()
    total_pizzas_sold = df['quantity'].sum()
    repeat_customers = df.groupby('order_id').size().value_counts().get(2, 0)

    # Sidebar with key metrics
    st.sidebar.header("Key Metrics")
    st.sidebar.metric("Total Orders", total_orders)
    st.sidebar.metric("Total Revenue", f"${total_revenue:,.2f}")
    st.sidebar.metric("Most Popular Size", most_popular_size)
    st.sidebar.metric("Most Popular Category", most_frequent_category)
    st.sidebar.metric("Total Pizzas Sold", total_pizzas_sold)
    st.sidebar.metric("Repeat Customers", repeat_customers)

    plots = [
        {"title": "Top Selling Pizzas (by Quantity)", "x": "pizza_name", "y": "quantity", "top": 5},
        {"title": "Quantity of Pizzas Sold by Category and Time of the Day", "x": "time_of_day", "hue": "pizza_category"},
        {"title": "Quantity of Pizzas Sold by Size and Time of the Day", "x": "time_of_day", "hue": "pizza_size"},
        {"title": "Monthly Revenue Trends by Pizza Category", "x": "order_month", "y": "total_price", "hue": "pizza_category", "estimator": "sum", "marker": "o"},
    ]

    for plot in plots:
        st.header(plot["title"])
        
        fig, ax = plt.subplots()
        
        if "Top" in plot["title"]:
          data = df.groupby(plot["x"])[plot["y"]].sum().reset_index().sort_values(by=plot["y"], ascending=False).head(plot["top"])
          ax.bar(data[plot["x"]].values, data[plot["y"]].values)
        
        if "Quantity" in plot["title"]:
          sns.countplot(x=plot["x"], hue=plot["hue"], data=df, ax=ax)
        
        if "Revenue" in plot["title"]:
          sns.lineplot(x=plot["x"], y=plot["y"], hue=plot["hue"], data=df, estimator=plot["estimator"], marker=plot["marker"], ax=ax)

        ax.set_xlabel(plot["x"].capitalize())
        ax.set_ylabel(plot["y"].capitalize())
        
        st.pyplot(fig)
    

if __name__ == "__main__":
    app()