Update app.py

app.py

@@ -452,6 +452,7 @@ def chart_11(disease_data):
 
 
 def chart_12(filtered_data):
+    st.write("4")
     graph_10 = filtered_data.copy()
     no_nan = graph_10.dropna(subset=['ImmunizationName'])
     immu = list(no_nan['ImmunizationName'])
@@ -931,7 +932,7 @@ def ML(filtered_data, scaler, unscaled_data):
     pca_df = pca.fit_transform(original_data[numerical_columns])
     d = list(original_data[numerical_columns].columns)
     pca_df = pd.DataFrame(pca_df, columns=d[:4])
-    
+    st.write("3")
     import plotly.graph_objects as go
 
     st.subheader("PCA")
@@ -996,6 +997,7 @@ def imputer(filtered_data):
     Ml_data = Ml_data.drop(columns=columns_drop)
     Ml_data = pd.concat([Ml_data, scaled_data], axis=1)
     Ml_data = Ml_data.convert_dtypes()  # change this to outlier_removed if you want outliwer to be removed
+    st.write("2")
     return ML(Ml_data, scaler, unscaled_data)
 
 
@@ -1054,6 +1056,7 @@ if analysis_option == 'Machine Learning':
         filtered_data = filtered_data[required_columns].copy()
         filtered_data = filtered_data.drop_duplicates().reset_index(drop=True)
         filtered_data = filtered_data.dropna(axis=1, how='all')
+        st.write("1")
         imputer(filtered_data)