Upload 3 files

app.py

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+import streamlit as st 
+import pandas as pd
+import joblib
+
+# heading 
+html_temp = """
+    <div style="background-color:black;padding:10px">
+    <h2 style="color:white;text-align:center;">Fraud Detection APP </h2>
+    </div>
+    """
+st.markdown(html_temp, unsafe_allow_html=True)
+
+# image
+url="https://tse2.mm.bing.net/th?id=OIP.ROc4vnkJBbKTf8uWRQpldAHaDt&pid=Api&P=0&h=180"
+st.image(url, use_container_width=True)
+
+@st.cache_data
+def convert_df(df):
+    return df.to_csv(index=False).encode("utf-8")
+
+
+# loading model
+model=joblib.load('iso_fraude_dection.joblib')
+
+# Required column in dataframe
+req_col= pd.DataFrame(columns=['step', 'type', 'amount'])
+
+# Download the template
+csv = convert_df(req_col)
+st.download_button(
+label="Download Template",
+data=csv,
+file_name="Template.csv",
+mime="text/csv")
+
+
+# uploading model
+file=st.file_uploader('Please Upload the CSV File', type=["csv"])
+col1, col2 = st.columns(2)
+if file is not None:
+    with col1:
+        df = pd.read_csv(file,encoding='ISO-8859-1')
+        st.write("Uploaded File Preview:")
+        st.dataframe(df.head()) 
+           
+    if st.button("Predict Outliers"):
+        try:
+            # Ensure required columns exist
+            required_columns = req_col
+            if not all(col in df.columns for col in required_columns):
+                st.error("Uploaded file does not match the required template structure.")
+            else:
+                predictions = model.predict(df)
+                with col2:
+                    df['Anomaly'] = ['Anomaly' if pred == -1 else 'Not Anomaly' for pred in predictions]
+                    st.write("Anomaly Detection Results:")
+                    st.dataframe(df.head())
+                    result_csv = convert_df(df)
+                    st.download_button(
+                    label="Download Results",
+                    data=result_csv,
+                    file_name="Anomaly_Detection_Results.csv",
+                    mime="text/csv")
+
+
+        except Exception as e:
+            st.error(f"An error occurred while processing the file: {e}")
+            
+

iso_fraude_dection.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d0b11487de440b38d90b3e1ccffdd906e30f9c83a64e393de8a0c6678c7eb4da
+size 1263000

requirements.txt

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+joblib==1.2.0
+matplotlib==3.7.1
+matplotlib-inline==0.1.6
+numpy==1.26.4
+pandas==1.5.3
+scikit-learn==1.6.0
+streamlit==1.41.1
+seaborn==0.12.2
+tabulate==0.8.10