# Import libraries
import streamlit as st
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import seaborn as sns

def run():
    # Load the dataset
    df = pd.read_csv("bquxjob_24b82863_18c2d385ce5.csv")

    # Create a sidebar
    st.sidebar.title("EDA Options")
    st.sidebar.subheader("Choose the features (Only choose 1)")

    # Create checkboxes for the features
    # Create radio buttons for the features
    selected_feature = st.sidebar.radio("Select Feature", ["limit_balance", "sex", "education_level", "marital_status", "age",
                                                        "pay_1", "bill_amt_1", "pay_amt_1", "default_payment_next_month"])

    # add sub-header
    st.sidebar.subheader("Choose the metrics for visualization (can choose multiple)")

    # Create a checkbox for the statistics
    stats = 0
    stats = st.sidebar.checkbox("Statistics")

    # Create a checkbox for the distribution
    dist = 0
    dist = st.sidebar.checkbox("Distribution")

    # Create a main title
    st.title("Exploratory Data Analysis on Default of Credit Card Clients Dataset")

    # Display the default text if no features are selected
    if stats == 0 and dist == 0:
        st.write("## Welcome to the EDA.")
        st.write("Please select the features and metrics that you want to explore from the sidebar.")

    else:
        # Display the statistics
        if stats:
            st.subheader("Statistics")
            st.write(df[selected_feature].describe())

        # Display the distribution
        if dist:
            st.subheader("Distribution")
            fig, ax = plt.subplots(figsize=(10, 6))
            sns.histplot(df[selected_feature], kde=True, bins=20)
            st.pyplot(fig)

if __name__ == '__main__':
    run()