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 by Saif Khan")
    df = load_data()
    
    total_orders = df['order_id'].nunique()    #function which can calculate the number of unique values
    total_revenue = df['total_price'].sum()  #function which can sum the column
    most_popular_size = df['pizza_size'].value_counts().idxmax()    #function which can get the maximum value 
    most_frequent_category = df['pizza_category'].value_counts().idxmax()    #function which can count of value of each product
    total_pizzas_sold = df['quantity'].sum()
   
    st.sidebar.header("Key Metrics")
    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("Total Orders", total_orders)
    plots = [
        {"title": "Top Selling Pizzas (by Quantity)", "x": "pizza_name", "y": "quantity", "top": 5},    #Write the appropriiate column as per the title given
        {"title": "Quantity of Pizzas Sold by Category and Time of the Day", "x": "time_of_day", "hue": "pizza_category"},   #Write the appropriiate column as per the title given
        {"title": "Quantity of Pizzas Sold by Size and Time of the Day", "x": "time_of_day", "hue": "pizza_size"},  #Write the appropriiate column as per the title given
        {"title": "Monthly Revenue Trends by Pizza Category", "x": "order_month", "y": "total_price", "hue": "pizza_category", "estimator": "sum", "marker": "o"}, #Write the appropriiate column as per the title given
    ]

    for plot in plots:
      st.header(plot["title"])
      
      fig, ax = plt.subplots()
      
      if "Top Selling Pizzas" in plot["title"]:
        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())
        ax.tick_params(axis='x', rotation=45)
      
      if "Quantity of Pizzas" in plot["title"]:
        sns.countplot(data=df, x=plot["x"], hue=plot["hue"], ax=ax)
          
      
      if "Monthly Revenue" 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)
    
if __name__ == "__main__":
    app()