import streamlit as st # type: ignore
import pandas as pd
import numpy as np


st.set_page_config(page_title="Wine Dataset Analysis", layout="wide")
#st.set_page_config(page_title="Wine Dataset Analysis", layout="wide")

# Custom CSS for styling
st.markdown("""
    <style>
    .main {
        background-color: #f5f5f5;
        color: #000000;
        font-family: Arial, sans-serif;
    }
    .stApp {
        background-image: url('https://www.google.com/url?sa=i&url=https%3A%2F%2Fwww.kaggle.com%2Fdatasets%2Fuciml%2Fred-wine-quality-cortez-et-al-2009&psig=AOvVaw044WbrqWBv67EgvsMbhuHe&ust=1724990459183000&source=images&cd=vfe&opi=89978449&ved=0CBQQjRxqFwoTCMCd2NqnmYgDFQAAAAAdAAAAABAE'); 
        background-size: cover;
        background-position: center;
        background-repeat: no-repeat;
    }
    .title {
        color: #ffffff;
        font-size: 50px;
        font-weight: bold;
        text-align: center;
        margin-top: 20px;
    }
    .subtitle {
        color: #ffffff;
        font-size: 20px;
        text-align: center;
        margin-bottom: 40px;
    }
    </style>
""", unsafe_allow_html=True)

# Background company name display
st.markdown(f"""
    <div class="stApp">
        <div class="title">Center for Analytics Services</div>
        <div class="subtitle">Association of Data Analysts and AI Professionals</div>
    </div>
""", unsafe_allow_html=True)

# App title
st.title("Wine Dataset Analysis")

# Number input for sample size
st.header("Number Input: Set Sample Size")
sample_size = st.number_input("Enter the number of samples to generate:", min_value=10, max_value=100, value=50)
st.write(f"Sample Size: {sample_size}")

# Sliders for feature selection
st.header("Sliders: Set Feature Values")
alcohol_level = st.slider("Alcohol Level", min_value=10.0, max_value=15.0, value=13.0, step=0.1)
malic_acid = st.slider("Malic Acid", min_value=0.5, max_value=5.0, value=2.5, step=0.1)
st.write(f"Selected Alcohol Level: {alcohol_level}")
st.write(f"Selected Malic Acid Level: {malic_acid}")

# Placeholder for dataset visualization (to be replaced with actual data later)
st.header("Dataset Visualization (Placeholder)")
data = pd.DataFrame({
    'Alcohol': np.random.normal(alcohol_level, 0.5, sample_size),
    'Malic.acid': np.random.normal(malic_acid, 0.5, sample_size),
    'Proline': np.random.randint(500, 1500, sample_size)
})
st.write(data)

# Line chart placeholder
st.header("Line Chart (Placeholder)")
st.line_chart(data[['Alcohol', 'Proline']])

# Custom footer with HTML and CSS
st.markdown("""
    <style>
    .footer {
        position: fixed;
        left: 0;
        bottom: 0;
        width: 100%;
        background-color: #4CAF50;
        color: white;
        text-align: center;
        padding: 10px;
        font-family: Arial, sans-serif;
    }
    </style>
    <div class="footer">
        © 2024 Center for Analytics Services, Association of Data Analysts and AI Professionals
    </div>
""", unsafe_allow_html=True)