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app.py

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+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": "Revenue by Pizza Category", "x": "pizza_category", "y": "total_price", "hue": "pizza_size"},
+        {"title": "Peak Order Times (by Hour)", "x": "order_time", "y": "quantity", "agg": "value_counts", "extract_hour": True},
+        {"title": "Monthly Revenue", "x": "order_month", "y": "total_price"}
+    ]
+
+    for plot in plots:
+        st.header(plot["title"])
+        if "agg" in plot:
+            data = getattr(df[plot["x"]], plot["agg"])().sort_values(ascending=False)
+        else:
+            data = df.groupby(plot["x"])[plot["y"]].sum().sort_values(ascending=False)
+        if "top" in plot:
+            data = data.head(plot["top"])
+        fig, ax = plt.subplots()
+        if plot["title"] == "Revenue by Pizza Category":
+          sns.barplot(x=plot["x"], y=plot["y"], hue=plot["hue"], data=data, ax=ax)
+        ax.bar(data.index, data.values)
+        ax.set_xlabel(plot["x"].capitalize())
+        ax.set_ylabel(plot["y"].capitalize())
+        if plot["title"] == "Monthly Revenue":
+            ax.set_xlabel("Month")
+        st.pyplot(fig)
+    
+
+if __name__ == "__main__":
+    app()

requirements.txt

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+pandas==1.5.2
+matplotlib==3.6.2
+seaborn==0.12.1
+scipy==1.10.0
+numpy==1.23.5