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import streamlit as st
import pandas as pd
import numpy as np
custom_css = """
<style>
html, body, [data-testid="stAppViewContainer"] {
background-image: linear-gradient(
rgba(0, 0, 0, 0.6),
rgba(0, 0, 0, 0.6)
),
url("https://www.istockphoto.com/photo/tech-or-space-background-abstract-3d-illustration-gm1367865109-437999705?utm_source=pixabay&utm_medium=affiliate&utm_campaign=SRP_photo_sponsored&utm_content=https%3A%2F%2Fpixabay.com%2Fphotos%2Fsearch%2Fbackground%2520datascience%2F&utm_term=background+datascience.jpg");
background-size: cover;
background-position: center;
background-repeat: no-repeat;
background-attachment: fixed;
color: white; /* Ensures all text is readable */
}
h2, h3 {
color: #FFD700; /* Gold color for headings */
}
p {
color: #FFFFFF; /* White text for paragraphs */
}
</style>
"""
# Inject the CSS into the app
st.markdown(custom_css, unsafe_allow_html=True)
st.markdown("<h2 style='text-align: center; color: Black;'>📊🔍What is Data </h2>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Raw facts, figures, or other information gathered for analysis, reference, or use in decision-making processes are called as data. It serves as the foundation for several processes in a variety of domains, such as machine learning, which uses to provide insights and train models."
"</p>",
unsafe_allow_html=True
)
st.markdown("Data can come in various forms, including text, numbers, images, videos, or signals, and is usually categorized into three main types:")
st.markdown("1. Structured data")
st.markdown("2. Unstructured data")
st.markdown("3. Semi-Structured data")
st.markdown("<h3 style='text-align: left; color: Black;'>📊Structured data </h3>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Organized in a predefined format, typically in rows and columns (e.g., spreadsheets, relational databases)."
"</p>",
unsafe_allow_html=True
)
st.markdown("<h3 style='text-align: left; color: Black;'>🖼️Unstructured data </h3>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Does not follow a predefined structure, such as text documents, images, and videos."
"</p>",
unsafe_allow_html=True
)
st.markdown("<h3 style='text-align: left; color: Black;'>🗂️Semi-Structured data </h3>", unsafe_allow_html=True)
st.markdown(
"<p style='font-size: 16px; color: White; font-style: italic;'>"
"Has elements of both structured and unstructured data, like JSON or XML files."
"</p>",
unsafe_allow_html=True
)
# Add buttons for each data type
if st.button("Learn More About Structured Data"):
st.markdown(
"<p style='font-size: 16px; color: White;'>Structured data is stored in a well-defined schema, such as tables or databases. Common examples include Excel files, CSV files, and SQL databases.</p>",
unsafe_allow_html=True
)
if st.button("Learn More About Unstructured Data"):
st.markdown(
"<p style='font-size: 16px; color: White;'>Unstructured data includes multimedia files, text documents, and other formats that lack a predefined schema. Examples are images, videos, and free-text files.</p>",
unsafe_allow_html=True
)
if st.button("Learn More About Semi-Structured Data"):
st.markdown(
"<p style='font-size: 16px; color: White;'>Semi-structured data lies between structured and unstructured data. Formats like JSON, XML, and YAML are common examples of semi-structured data.</p>",
unsafe_allow_html=True
)
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