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# Import necessary libraries
import pandas as pd
import streamlit as st

# Simulated functions to gather data
def gather_professions():
    # Simulated data; replace this with actual data collection logic
    professions_data = {
        'Profession': ['Engineer', 'Doctor', 'Artist', 'Scientist', 'Teacher'],
        'Field': ['Engineering', 'Medicine', 'Arts', 'Science', 'Education'],
        'Emerging': [False, False, True, True, False]
    }
    return pd.DataFrame(professions_data)

def gather_universities():
    # Simulated data; replace this with actual data collection logic
    universities_data = {
        'University': ['University A', 'University B', 'University C'],
        'URL': ['https://university-a.edu', 'https://university-b.edu', 'https://university-c.edu'],
        'Region': ['North America', 'Europe', 'Asia'],
        'Field of Study': ['Engineering', 'Arts', 'Medicine']
    }
    return pd.DataFrame(universities_data)

# Gather data
professions_df = gather_professions()
universities_df = gather_universities()

# Data Cleaning & Preprocessing
def clean_data(df):
    # Remove duplicates and fill missing values
    df = df.drop_duplicates()
    df = df.fillna('N/A')
    return df

# Clean data
professions_df = clean_data(professions_df)
universities_df = clean_data(universities_df)

# Streamlit application
def run_app():
    st.title("Career Guidance Application")
    
    # Profession Search
    st.header("Search for Professions")
    profession_search = st.text_input("Enter a profession:")
    if profession_search:
        results = professions_df[professions_df['Profession'].str.contains(profession_search, case=False)]
        st.write(results)
    
    # University Directory
    st.header("University Directory")
    region_filter = st.selectbox("Select a region", universities_df['Region'].unique())
    filtered_universities = universities_df[universities_df['Region'] == region_filter]
    st.write(filtered_universities)

    # Q&A Functionality
    st.header("Q&A")
    question = st.text_input("Ask a question about your career:")
    if question:
        # Simulated response; replace this with an actual Q&A logic or API call
        st.write(f"You asked: {question}. Here are some resources to explore...")

# Run Streamlit app
if __name__ == "__main__":
    run_app()