Hugging Face's logo Hugging Face Search models, datasets, users... Models Datasets Spaces Posts Docs Enterprise Pricing Hugging Face is way more fun with friends and colleagues! 🤗 Join an organization Spaces: danielle2003 / danielleAnge like 0 App Files Community Settings danielleAnge / dash.py danielle2003's picture danielle2003 commit name ae51f3b about 3 hours ago raw Copy download link history blame edit delete 1.24 kB 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()