pages/introds.py

import streamlit as st  # Aliased streamlit as 'st' for consistency
import pandas as pd
import numpy as np

# Header Section
st.markdown(
    "<h1 style='text-align: center; color: Black;'>DATA SCIENCE INTRODUCTION</h1>",
    unsafe_allow_html=True
)

# Main Content Section
st.markdown(
    """
    <h2 style='color: Black;'>What is Data Science</h2>
     
 
        <p>
           It combines techniques from statistics, computer science, mathematics, and domain expertise to analyze and interpret data effectively.
           In essence, data science transforms raw data into actionable insights, driving smarter decisions across industries.
           There are several types of applications, as explained below:
        </p>
        <ul>
            <li>Analyzing customer reviews to identify product sentiment</li> 
            <li>Techniques Used: Natural Language Processing (NLP), sentiment analysis.</li>
            <li>Optimizing delivery routes for logistics companies</li>
            <li>Techniques Used: Graph algorithms, optimization techniques.</li>
        </ul>
    </div>

    <div class="section">
        <h2>Few Important Steps in Data Science</h2>
        <p>
            Data Science involves several steps, such as:
        </p>
        <ul>    
             <li><strong>Understanding the Given Problem:</strong> First, you need to understand the type of problem you are addressing.</li>
             <li><strong>Data Collection:</strong> Gather relevant data from various sources to address the defined problem.</li>
             <li><strong>Data Cleaning and Preprocessing:</strong> Prepare the raw data for analysis by handling inconsistencies, missing values, and errors.</li>
             <li><strong>Exploratory Data Analysis (EDA):</strong> Gain an initial understanding of the data's main characteristics through visualization and summary statistics.</li>
             <li><strong>Deployment:</strong> Implement the model into a production environment where it can provide actionable insights or make decisions in real-time.</li>
        </ul>
    </div>
    """,
    unsafe_allow_html=True
)