import streamlit as st
import pandas as pd

# Define function to read CSV file
def read_data():
    data = pd.read_csv("health_conditions.csv")
    return data

# Define function to update CSV file
def update_data(data):
    data.to_csv("health_conditions.csv", index=False)

# Define function to display data
def display_data(data):
    st.write(data)

# Define function to add new data
def add_data(data, new_data):
    data = pd.concat([data, new_data], ignore_index=True)
    return data

# Define function to delete data
def delete_data(data, indices):
    data = data.drop(indices, axis=0)
    data = data.reset_index(drop=True)
    return data

# Define function to download data as CSV file
def download_data(data):
    csv = data.to_csv(index=False)
    href = f'<a href="data:file/csv;base64,{base64.b64encode(csv.encode()).decode()}" download="health_conditions.csv">Download CSV file</a>'
    return href

# Define main function
def main():
    st.title("Health Condition Costs Visualization")
    data = read_data()
    display_data(data)
    st.write("To add new data, please fill in the form below:")
    condition = st.text_input("Condition")
    icd10_code = st.text_input("ICD10 Code")
    snomed_code = st.text_input("SNOMED Code")
    loinc_code = st.text_input("LOINC Code")
    assessment = st.text_input("Assessment")
    if st.button("Add"):
        new_data = pd.DataFrame({
            "condition": [condition],
            "ICD10_code": [icd10_code],
            "SNOMED_code": [snomed_code],
            "LOINC_code": [loinc_code],
            "assessment": [assessment]
        })
        data = add_data(data, new_data)
        update_data(data)
    indices = []
    for i, row in data.iterrows():
        if st.checkbox(f"Delete row {i+1}"):
            indices.append(i)
    if len(indices) > 0:
        data = delete_data(data, indices)
        update_data(data)
    st.markdown(download_data(data), unsafe_allow_html=True)

if __name__ == "__main__":
    main()