app.py

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_pizza_size = df['pizza_size'].value_counts().idxmax()
    most_frequent_pizza_category = df['pizza_category'].value_counts().idxmax()
    total_pizzas_sold = df['pizza_id'].nunique()

    # Sidebar with key metrics
    st.sidebar.header('Key Metrics')
    st.sidebar.metric('Total Orders', total_orders)
    st.sidebar.metric('Total Pizzas Sold', total_pizzas_sold)
    st.sidebar.metric('Total Revenue', f'${total_revenue:,.2f}')
    st.sidebar.metric('Most Popular Pizza Size', most_popular_pizza_size)
    st.sidebar.metric('Most Frequent Pizza Category', most_frequent_pizza_category)
    
    # Provide the details of the plots here
    plots = [
        {"title": "Total Pizzas Sold by Pizza Size and Categories", "x": "pizza_size", "hue": "pizza_category"},
        {"title": "Monthly Revenue Trends by Pizza Size", "x": "order_month", "y": "total_revenue", "hue": "pizza_size", "estimator": "sum", "marker": "o"},
        {"title": "Monthly Revenue Trends by Pizza Category", "x": "order_month", "y": "total_revenue", "hue": "pizza_category", "estimator": "sum", "marker": "o"},
        {"title": "Total Revenue by Pizza Category", "x": "pizza_category", "y": "total_revenue", "estimator": "sum"},
    ]

    for plot in plots:
        st.header(plot["title"])
      
        fig, ax = plt.subplots()

        if "Total Pizzas Sold" in plot["title"] and "y" in plot:
            data_aux = df.groupby(plot["x"])[plot["y"]].sum().reset_index().sort_values(by=plot["y"], ascending=False).head(plot["top"])
            ax.bar(data_aux[plot["x"]].values.tolist(), data_aux[plot["y"]].values.tolist())
        
        if "Pizza Size" in plot["title"]:
            sns.countplot(data=df, x=plot["x"], hue=plot["hue"], ax=ax)
        
        if "Pizza Category" in plot["title"]:
            sns.lineplot(data=df, x=plot["x"], y=plot["y"], hue=plot["hue"], estimator=plot["estimator"], errorbar=None, marker=plot["marker"], ax=ax)

        ax.set_xlabel(" ".join(plot["x"].split("_")).capitalize())
        if "y" in plot.keys():
            ax.set_ylabel(" ".join(plot["y"].split("_")).capitalize())
        else:
            ax.set_ylabel("Quantity")
        ax.legend(bbox_to_anchor=(1,1))
      
        st.pyplot(fig)
        plt.show()
    

if __name__ == "__main__":
    app()