import time
import plotly.express as px
import pandas as pd
import numpy as np
import streamlit as st

df = pd.read_csv('bank.csv')


st.set_page_config(page_title="Bank Data", page_icon="", layout="wide")

st.title("Bank Data Analysis")

job_filter = st.selectbox('Select Job', pd.unique(df['job']))

df_filtered = df[df['job'] == job_filter]

avg_age = np.mean(df_filtered['age'])
count_married = int(df_filtered['marital'].value_counts()['married'])

kp1, kp2, kp3 = st.columns(3)

kp1.metric(label="Average Age", value=round(avg_age), delta=round(avg_age) - 10)
kp2.metric(label="Married Count", value=count_married, delta=None)

st.subheader("Age vs Marital Status")
fig = px.density_heatmap(df_filtered, x="age", y="marital", nbinsx=20, nbinsy=5, color_continuous_scale="Blues")
st.plotly_chart(fig, use_container_width=True)
fig_col1,fig_col2 = st.columns(2)
with fig_col1:
    st.markdown('### first chart')
    fig1 = px.density_heatmap(data_frame = df,y='age',x='marital')
    st.write(fig1)
with fig_col2:
    st.markdown('### first chart')
    fig1 = px.histogram(data_frame = df,x='age')
    st.write(fig2)
st.dataframe(df)
st.markdown('### charts')

def main():
    st.header("welcome")

if __name__ == "__main__":
    main()