import streamlit as st import pandas as pd import numpy as np custom_css = """ """ # Inject the CSS into the app st.markdown(custom_css, unsafe_allow_html=True) st.markdown("
" "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." "
", 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("" "Organized in a predefined format, typically in rows and columns (e.g., spreadsheets, relational databases)." "
", unsafe_allow_html=True ) st.markdown("" "Does not follow a predefined structure, such as text documents, images, and videos." "
", unsafe_allow_html=True ) st.markdown("" "Has elements of both structured and unstructured data, like JSON or XML files." "
", unsafe_allow_html=True ) # Add buttons for each data type if st.button("Structured data is stored in a well-defined schema, such as tables or databases. Common examples include Excel files, CSV files, and SQL databases.
", unsafe_allow_html=True ) if st.button("Learn More About Unstructured Data"): st.markdown( "Unstructured data includes multimedia files, text documents, and other formats that lack a predefined schema. Examples are images, videos, and free-text files.
", unsafe_allow_html=True ) if st.button("Learn More About Semi-Structured Data"): st.markdown( "Semi-structured data lies between structured and unstructured data. Formats like JSON, XML, and YAML are common examples of semi-structured data.
", unsafe_allow_html=True )