Code Editor for app.py

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

# Set page config to wide mode
st.set_page_config(layout="wide")

# Create sample data
def generate_sample_data():
    np.random.seed(42)
    dates = pd.date_range(start='2023-01-01', end='2023-12-31', freq='D')
    categories = ['Category A', 'Category B', 'Category C']
    
    data = []
    for date in dates:
        for category in categories:
            value = np.random.randint(100, 1000)
            data.append({
                'date': date,
                'category': category,
                'value': value
            })
    
    return pd.DataFrame(data)

# Create the main dataframe
df = generate_sample_data()

# Create two columns for the layout
col1, col2 = st.columns([1, 2])

# Filters column
with col1:
    st.markdown("### Filters")
    
    # Date range filter
    date_range = st.date_input(
        "Select Date Range",
        value=(df['date'].min(), df['date'].max()),
        min_value=df['date'].min(),
        max_value=df['date'].max()
    )
    
    # Category filter
    categories = st.multiselect(
        "Select Categories",
        options=df['category'].unique(),
        default=df['category'].unique()
    )

# Filter the data based on selections
filtered_df = df[
    (df['date'] >= pd.Timestamp(date_range[0])) &
    (df['date'] <= pd.Timestamp(date_range[1])) &
    (df['category'].isin(categories))
]

# Chart column
with col2:
    st.markdown("### Chart")
    
    # Aggregate data by category
    chart_data = filtered_df.groupby('category')['value'].sum().reset_index()
    
    # Create bar chart
    st.bar_chart(
        data=chart_data,
        x='category',
        y='value',
        use_container_width=True
    )