Code Editor for app.py

import streamlit as st
from PIL import Image
import pandas as pd
import numpy as np

# Initialize session state
if 'logged_in' not in st.session_state:
    st.session_state.logged_in = False

# Page config
st.set_page_config(page_title="Dashboard", layout="wide")

# Load and display logo
logo = Image.new('RGB', (200, 100), 'blue')  # Placeholder logo

def login():
    st.image(logo, width=200)
    st.title("Welcome to Dashboard")
    
    username = st.text_input("Username")
    password = st.text_input("Password", type="password")
    
    if st.button("Login"):
        if username == "admin" and password == "admin":  # Simple validation
            st.session_state.logged_in = True
            st.rerun()
        else:
            st.error("Invalid credentials")

def main():
    # Sidebar
    with st.sidebar:
        st.image(logo, width=150)
        st.title("Dashboard")
        
        # Menu buttons
        selected = st.radio("Menu", ["Sales", "Inventory", "Analytics"])
    
    # Main content
    if selected == "Sales":
        show_sales_dashboard()
    elif selected == "Inventory":
        show_inventory_dashboard()
    else:
        show_analytics_dashboard()

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,
        'Category': np.random.choice(['Electronics', 'Clothing', 'Food', 'Books'], size=len(dates)),
        'Sales': np.random.randint(100, 1000, size=len(dates)),
        'Quantity': np.random.randint(10, 100, size=len(dates))
    }
    return pd.DataFrame(data)

def show_sales_dashboard():
    st.title("Sales Dashboard")
    
    # Filters
    col1, col2 = st.columns(2)
    with col1:
        category = st.multiselect("Category", ["Electronics", "Clothing", "Food", "Books"])
    with col2:
        date_range = st.date_input("Date Range", value=(pd.to_datetime('2023-01-01'), pd.to_datetime('2023-12-31')))
    
    # Load data
    df = generate_sample_data()
    
    # Apply filters
    if category:
        df = df[df['Category'].isin(category)]
    df = df[(df['Date'] >= pd.to_datetime(date_range[0])) & (df['Date'] <= pd.to_datetime(date_range[1]))]
    
    # Pie chart
    pie_data = df.groupby('Category')['Sales'].sum()
    st.subheader("Sales by Category")
    st.pie_chart(pie_data)
    
    # Summary DataFrame
    st.subheader("Summary")
    summary = df.groupby('Category').agg({
        'Sales': ['sum', 'mean'],
        'Quantity': ['sum', 'mean']
    }).round(2)
    st.dataframe(summary)
    
    # Complete data
    st.subheader("Detailed Data")
    st.dataframe(df)

def show_inventory_dashboard():
    st.title("Inventory Dashboard")
    st.info("Inventory dashboard content will be displayed here")

def show_analytics_dashboard():
    st.title("Analytics Dashboard")
    st.info("Analytics dashboard content will be displayed here")

# Main app logic
if not st.session_state.logged_in:
    login()
else:
    main()