Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
from datetime import datetime, timedelta

# Set page config
st.set_page_config(page_title="Excel Dashboard", layout="wide")

# Generate sample data
@st.cache_data
def generate_sample_data():
    np.random.seed(42)
    dates = pd.date_range(start='2023-01-01', end='2023-12-31', freq='D')
    
    data = {
        'Date': dates,
        'Sales': np.random.uniform(1000, 5000, len(dates)),
        'Customers': np.random.randint(50, 200, len(dates)),
        'Orders': np.random.randint(100, 400, len(dates)),
        'Region': np.random.choice(['North', 'South', 'East', 'West'], len(dates))
    }
    
    df = pd.DataFrame(data)
    return df

df = generate_sample_data()

# Header
st.title("📊 Business Analytics Dashboard")
st.markdown("---")

# KPI Metrics
col1, col2, col3, col4 = st.columns(4)

with col1:
    total_sales = df['Sales'].sum()
    st.metric("Total Sales", f"${total_sales:,.2f}")

with col2:
    total_customers = df['Customers'].sum()
    st.metric("Total Customers", f"{total_customers:,}")

with col3:
    total_orders = df['Orders'].sum()
    st.metric("Total Orders", f"{total_orders:,}")

with col4:
    avg_order_value = total_sales / total_orders
    st.metric("Avg Order Value", f"${avg_order_value:.2f}")

st.markdown("---")

# Charts
col1, col2 = st.columns(2)

with col1:
    # Sales Trend
    sales_trend = px.line(df, x='Date', y='Sales', 
                         title='Daily Sales Trend',
                         labels={'Sales': 'Sales ($)', 'Date': 'Date'})
    st.plotly_chart(sales_trend, use_container_width=True)

    # Customer Distribution by Region
    region_dist = px.pie(df, names='Region', 
                        values='Customers',
                        title='Customer Distribution by Region')
    st.plotly_chart(region_dist, use_container_width=True)

with col2:
    # Orders vs Customers Scatter
    scatter = px.scatter(df, x='Customers', y='Orders',
                        title='Orders vs Customers Correlation',
                        trendline="ols")
    st.plotly_chart(scatter, use_container_width=True)

    # Monthly Sales Box Plot
    df['Month'] = df['Date'].dt.strftime('%B')
    monthly_box = px.box(df, x='Month', y='Sales',
                        title='Monthly Sales Distribution',
                        labels={'Sales': 'Sales ($)'})
    st.plotly_chart(monthly_box, use_container_width=True)

# Data Table
st.markdown("---")
st.subheader("Raw Data")
st.dataframe(df, use_container_width=True)

# Download Button
csv = df.to_csv(index=False).encode('utf-8')
st.download_button(
    label="Download Data as CSV",
    data=csv,
    file_name="dashboard_data.csv",
    mime="text/csv",
)