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import streamlit as st | |
import pandas as pd | |
import plotly.express as px | |
# Define the data | |
data = pd.DataFrame({ | |
'Illness': ['Anxiety', 'Depression', 'Diabetes', 'Heart Disease'], | |
'Cost (Billion USD)': [42, 210, 327, 219] | |
}) | |
# Define the sunburst plot | |
fig = px.sunburst( | |
data, | |
path=['Illness'], | |
values='Cost (Billion USD)', | |
color='Cost (Billion USD)', | |
color_continuous_scale='reds' | |
) | |
# Define the Streamlit app | |
st.title('Cost of Illnesses in Billion USD per Year') | |
st.plotly_chart(fig, use_container_width=True) | |
# Define the data | |
data = pd.DataFrame({ | |
'Illness': ['Anxiety π°', 'Depression π', 'Diabetes π©Έ', 'Heart Disease π'], | |
'SNOMED': ['35398006', '35489007', '73211009', '53741008'], | |
'CPT Code': ['90834, 90837, 90847', '90785, 90832, 90834', '82947, 82948, 82950', '93000, 93010, 93015'], | |
'ICD10': ['F41.1', 'F32.9', 'E11.9', 'I50.9'], | |
'LOINC': ['59284-0', '72166-2', '4548-4', '8616-5'] | |
}) | |
# Define the Streamlit app | |
st.title('Codes for Illnesses') | |
st.table(data) | |