Update app.py

app.py

@@ -52,9 +52,6 @@ if page == "Clustering Analysis":
     all_files = os.listdir(directory)
     # Filter files to only include CSV files
     csv_files = [file for file in all_files if file.endswith(".csv")]
-    st.write("CSV files in the directory:")
-    for file in csv_files:
-        st.write(file)
 
     # Select a CSV file from the list
     selected_csv = st.selectbox("Select a CSV file from the list", ["None"] + csv_files)
@@ -135,7 +132,16 @@ elif page == "Anomaly Detection":
     # import AnomalyExperiment
     from pycaret.anomaly import AnomalyExperiment
 
-        # Upload the CSV file
+    # Display the list of CSV files
+    directory = "./"
+    all_files = os.listdir(directory)
+    # Filter files to only include CSV files
+    csv_files = [file for file in all_files if file.endswith(".csv")]
+
+    # Select a CSV file from the list
+    selected_csv = st.selectbox("Select a CSV file from the list", ["None"] + csv_files)
+    
+    # Upload the CSV file
     uploaded_file = st.file_uploader("Choose a CSV file", type="csv")
 
     # Define the unsupervised model
@@ -143,13 +149,16 @@ elif page == "Anomaly Detection":
     selected_model = st.selectbox("Choose an anomaly model", anomalymodel)
 
     # Read and display the CSV file
-    if uploaded_file is not None:
-        try:
-            delimiter = ','
-            insurance_claims = pd.read_csv (uploaded_file, sep=delimiter)
-        except ValueError:
-            delimiter = '|'
-            insurance_claims = pd.read_csv (uploaded_file, sep=delimiter, encoding='latin-1')
+    if selected_csv != "None" or uploaded_file is not None:
+        if uploaded_file:
+            try:
+                delimiter = ','
+                insurance_claims = pd.read_csv (uploaded_file, sep=delimiter)
+            except ValueError:
+                delimiter = '|'
+                insurance_claims = pd.read_csv (uploaded_file, sep=delimiter, encoding='latin-1')
+        else:
+            insurance_claims = pd.read_csv(selected_csv)
         
         s = setup(insurance_claims, session_id = 123)