Code Editor for app.py

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

# Generate sample data
def generate_sample_data():
    np.random.seed(42)
    data = {
        'Name': [f'Person {i}' for i in range(1, 11)],
        'Age': np.random.randint(20, 70, 10),
        'Salary': np.random.randint(30000, 120000, 10),
        'Experience': np.random.randint(1, 20, 10),
        'Department': np.random.choice(['HR', 'IT', 'Sales', 'Marketing'], 10)
    }
    return pd.DataFrame(data)

# Create the dataframe
df = generate_sample_data()

# Title
st.title('DataFrame Column Selector')

# Sidebar for column selection
st.sidebar.header('Column Selection')

# Get all column names
all_columns = df.columns.tolist()

# Radio button to choose between include or exclude mode
selection_mode = st.sidebar.radio(
    "Selection Mode",
    ["Include Columns", "Exclude Columns"]
)

if selection_mode == "Include Columns":
    # Multi-select for columns to include
    selected_columns = st.sidebar.multiselect(
        "Select columns to include",
        all_columns,
        default=all_columns
    )
    if not selected_columns:
        st.warning("Please select at least one column to display")
    else:
        st.dataframe(df[selected_columns])
else:
    # Multi-select for columns to exclude
    excluded_columns = st.sidebar.multiselect(
        "Select columns to exclude",
        all_columns,
        default=[]
    )
    selected_columns = [col for col in all_columns if col not in excluded_columns]
    st.dataframe(df[selected_columns])

# Display some statistics
st.header('Data Statistics')
if selected_columns:
    st.write(df[selected_columns].describe())