pages/3_Identity_Theft.py

import streamlit as st
from utils import AgeAnalysis



age_analytics = AgeAnalysis()




st.markdown("#####  Identity theft")
st.caption("Identity theft occurs when someone uses another person's personal identifying information, like their name, identifying number, or credit card number, without their permission, to commit fraud or other crimes.")
st.markdown("""
* :violet[Minimum age in the dataset is **19**]
* :violet[Maximum age in the dataset is **99**]
* Fraudulent Transactions made by :orange[age group 80+] could be considered **identity theft**
""")
age_category, query_result = st.columns([0.3,0.7])
with age_category:
    query = st.radio(
        label="Choose the age block", 
        options=['Less than 25', 'Between 25 and 50', 'Below 50', 
                 'Above 50', 'Between 50 and 60', 'Above 60', 'Above 80']
    )
with query_result:
    with st.spinner("⏳Querying..."):
        response_data, fig = age_analytics.age_realted_query(query)
        st.pyplot(fig=fig, use_container_width=True)
st.markdown(
    f"""
    * Number of Transactions made by age block:`{query}` is :blue[{response_data.shape[0]}]
    * Number of Fraudulent Transaction made by age block:`{query}` is 
    :red[{response_data.query("Fraud=='Yes'").shape[0]}]
    """)