Code Editor for app.py

import streamlit as st
import pandas as pd
import numpy as np

st.title("Report Generator")

# Sidebar inputs
st.sidebar.header("Report Parameters")
report_type = st.sidebar.selectbox(
    "Report Type",
    ["Sales Analysis", "Customer Demographics", "Product Performance"]
)

date_range = st.sidebar.date_input(
    "Date Range",
    value=(pd.Timestamp("2023-01-01"), pd.Timestamp("2023-12-31"))
)

# Generate sample data based on inputs
def generate_sample_data(report_type, start_date, end_date):
    date_range = pd.date_range(start_date, end_date, freq='D')
    n_samples = len(date_range)
    
    if report_type == "Sales Analysis":
        data = {
            'Date': date_range,
            'Revenue': np.random.uniform(1000, 5000, n_samples),
            'Units_Sold': np.random.randint(50, 200, n_samples),
            'Profit_Margin': np.random.uniform(0.15, 0.35, n_samples)
        }
    elif report_type == "Customer Demographics":
        data = {
            'Date': date_range,
            'New_Customers': np.random.randint(10, 50, n_samples),
            'Customer_Age': np.random.uniform(25, 45, n_samples),
            'Customer_Satisfaction': np.random.uniform(3.5, 4.8, n_samples)
        }
    else:  # Product Performance
        data = {
            'Date': date_range,
            'Product_Views': np.random.randint(500, 2000, n_samples),
            'Conversion_Rate': np.random.uniform(0.02, 0.08, n_samples),
            'Returns': np.random.randint(1, 10, n_samples)
        }
    
    return pd.DataFrame(data)

# Generate report when user clicks button
if st.sidebar.button("Generate Report"):
    df = generate_sample_data(report_type, date_range[0], date_range[1])
    
    st.header(f"{report_type} Report")
    st.subheader(f"Period: {date_range[0]} to {date_range[1]}")
    
    # Display summary statistics
    st.subheader("Summary Statistics")
    st.table(df.describe().round(2))
    
    # Display time series chart
    st.subheader("Time Series Analysis")
    numeric_cols = df.select_dtypes(include=[np.number]).columns
    chart_col = st.selectbox("Select metric to visualize", numeric_cols)
    
    st.line_chart(df.set_index('Date')[chart_col])
    
    # Display raw data
    st.subheader("Raw Data")
    st.dataframe(df)
    
    # Download button
    csv = df.to_csv(index=False)
    st.download_button(
        label="Download Report as CSV",
        data=csv,
        file_name=f"{report_type.lower().replace(' ', '_')}_report.csv",
        mime='text/csv',
    )
else:
    st.info("Please set the parameters and click 'Generate Report' to create a report.")