Update pages/2_Data Cleaning and Processing .py

pages/2_Data Cleaning and Processing .py

@@ -711,15 +711,15 @@ if df is not None:
     # Drop rows where price is greater than 40000
     # Check if the 'price' column exists
     if 'price' in df.columns:
-    st.write("### Original Dataset")
-    st.write(df['price'].describe())  # Use describe() for a summary of the 'price' column
-    
-    # Filter rows where price is less than 600 or greater than 40,000
-    df_filtered = df[(df['price'] < 600) | (df['price'] > 40000)]
-    df.drop(df_filtered.index, inplace=True)  # Drop rows based on the filtered indices
-    
-    st.write("### Updated Dataset with Filtered Rows")
-    st.write(df['price'].describe())  # Display summary of the updated 'price' column
+        st.write("### Original Dataset")
+        st.write(df['price'].describe())  # Use describe() for a summary of the 'price' column
+        
+        # Filter rows where price is less than 600 or greater than 40,000
+        df_filtered = df[(df['price'] < 600) | (df['price'] > 40000)]
+        df.drop(df_filtered.index, inplace=True)  # Drop rows based on the filtered indices
+        
+        st.write("### Updated Dataset with Filtered Rows")
+        st.write(df['price'].describe())  # Display summary of the updated 'price' column
     # Redirect the output of df.info() to a string buffer
     buffer = StringIO()
     df.info(buf=buffer)