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| import streamlit as st | |
| import pandas as pd | |
| import plotly.express as px | |
| from streamlit_lottie import st_lottie | |
| import requests | |
| import ast | |
| # Set page config at the very beginning | |
| st.set_page_config(page_title="Health Explorer", page_icon="🩺", layout="wide") | |
| # Function to load Lottie animation | |
| def load_lottieurl(url: str): | |
| r = requests.get(url) | |
| if r.status_code != 200: | |
| return None | |
| return r.json() | |
| # Load DataFrame | |
| def load_data(): | |
| df = pd.read_csv('disease.csv') | |
| # Convert string representations of lists to actual lists | |
| df['symptom'] = df['symptom'].apply(ast.literal_eval) | |
| df['aurvedic_treatments'] = df['aurvedic_treatments'].apply(ast.literal_eval) | |
| return df | |
| # Load data | |
| df = load_data() | |
| # Sidebar | |
| st.sidebar.title("Health Explorer 🩺") | |
| page = st.sidebar.radio("Navigate", ["Home", "Disease Search", "Statistics"]) | |
| if page == "Home": | |
| st.title("Welcome to Health Explorer") | |
| col1, col2 = st.columns([2, 1]) | |
| with col1: | |
| st.markdown(""" | |
| Explore information about various diseases, their treatments, and prevention methods. | |
| Use the sidebar to navigate through different sections of the app. | |
| - **Disease Search**: Look up specific diseases and get detailed information. | |
| - **Statistics**: View overall statistics about the diseases in our database. | |
| """) | |
| with col2: | |
| lottie_health = load_lottieurl("https://assets1.lottiefiles.com/packages/lf20_5njp3vgg.json") | |
| st_lottie(lottie_health, height=200) | |
| elif page == "Disease Search": | |
| st.title("Disease Information Search") | |
| # Input search query with suggestions from the Disease column | |
| search_query = st.text_input("Start typing a disease name...", "") | |
| # Generate suggestions dynamically based on input | |
| if search_query: | |
| suggestions = df[df['Disease'].str.contains(search_query, case=False)]['Disease'].tolist() | |
| else: | |
| suggestions = df['Disease'].tolist() | |
| # Show suggestions in a selectbox (if suggestions exist) | |
| selected_disease = st.selectbox("Search results:", suggestions) | |
| # If a disease is selected, display the details | |
| if selected_disease: | |
| result = df[df['Disease'] == selected_disease] | |
| for index, row in result.iterrows(): | |
| st.header(row['Disease']) | |
| col1, col2 = st.columns(2) | |
| with col1: | |
| st.subheader("Treatment") | |
| st.info(row['treatment']) | |
| st.subheader("Prevention") | |
| st.success(row['prevention']) | |
| with col2: | |
| st.subheader("Symptoms") | |
| for symptom in row['symptom']: | |
| st.warning(f"• {symptom}") | |
| st.subheader("Ayurvedic Treatments") | |
| for treatment in row['aurvedic_treatments']: | |
| st.info(f"• {treatment}") | |
| # Word cloud of symptoms | |
| try: | |
| from wordcloud import WordCloud | |
| import matplotlib.pyplot as plt | |
| wordcloud = WordCloud(width=800, height=400, background_color='white').generate(' '.join(row['symptom'])) | |
| plt.figure(figsize=(10, 5)) | |
| plt.imshow(wordcloud, interpolation='bilinear') | |
| plt.axis('off') | |
| st.pyplot(plt) | |
| except ImportError: | |
| st.write("Word cloud visualization is not available.") | |
| elif page == "Statistics": | |
| st.title("Disease Statistics") | |
| # Count of diseases by treatment type | |
| treatment_counts = df['treatment'].value_counts() | |
| fig = px.pie(values=treatment_counts.values, names=treatment_counts.index, title="Distribution of Treatment Types") | |
| st.plotly_chart(fig) | |
| # Top 10 most common symptoms | |
| all_symptoms = [symptom for symptoms in df['symptom'] for symptom in symptoms] | |
| symptom_counts = pd.Series(all_symptoms).value_counts().head(10) | |
| fig = px.bar(x=symptom_counts.index, y=symptom_counts.values, title="Top 10 Most Common Symptoms") | |
| fig.update_xaxes(title="Symptom") | |
| fig.update_yaxes(title="Frequency") | |
| st.plotly_chart(fig) | |
| # Footer | |
| st.sidebar.markdown("---") | |
| st.sidebar.info("Created with ❤️ by [Sumit Yadav](sumityadav.com.np)") |