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import streamlit as st | |
import process | |
import pandas as pd | |
st.set_page_config(page_title="Data Anonymizer App") | |
st.title("Data Anonymizer App") | |
st.sidebar.title("Data Upload") | |
uploaded_file = st.sidebar.file_uploader("Choose a CSV file", type="csv") | |
if uploaded_file: | |
df = pd.read_csv(uploaded_file) | |
st.write("Original Data:") | |
st.write(df) | |
# process the data | |
processed_df, sensitive_cols = process.process_data(df) | |
# display processed data | |
st.write("Processed Data:") | |
st.write(processed_df) | |
# ask for sensitive columns removal | |
if sensitive_cols: | |
st.write(f"The following columns contain sensitive data: {', '.join(sensitive_cols)}") | |
if st.checkbox("Remove sensitive columns"): | |
processed_df.drop(columns=sensitive_cols, inplace=True) | |
else: | |
st.write("Sensitive columns will not be removed.") | |
# ask for k-anonymity | |
if st.checkbox("Apply k-anonymity"): | |
k = st.number_input("Enter the value of k", min_value=1) | |
processed_df = process.apply_k_anonymity(processed_df, k) | |
st.write("Final Processed Data:") | |
st.write(processed_df) | |