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a6a7246 1bafc48 a6a7246 1bafc48 a6a7246 1bafc48 8984162 5014e5f 1bafc48 a6a7246 1bafc48 a6a7246 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | 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()
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