Create app.py

app.py

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+import streamlit as st
+import pandas as pd
+
+# Sample DataFrame for demonstration
+data = {
+    'product_code': [1, 2, 3, 4, 5],
+    'label': ['Label1', 'Label2', 'Label3', 'Label4', 'Label1'],
+    'amount': [250, 450, 300, 200, 500]
+}
+df = pd.DataFrame(data)
+
+# Streamlit App
+st.title('DataFrame Column Selector')
+
+# Display the original DataFrame
+st.subheader('Original DataFrame')
+st.write(df)
+
+# Column selection for inclusion
+st.subheader('Select Columns to Include')
+include_columns = st.multiselect('Select columns to include', options=df.columns, default=df.columns.tolist())
+
+# Column selection for exclusion
+st.subheader('Select Columns to Exclude')
+exclude_columns = st.multiselect('Select columns to exclude', options=df.columns, default=[])
+
+# Filter DataFrame to include only selected columns
+if include_columns:
+    filtered_df = df[include_columns]
+else:
+    filtered_df = df
+
+# Further filter DataFrame to exclude specified rows
+if exclude_columns:
+    filtered_df = filtered_df[~filtered_df[exclude_columns].apply(lambda x: x.isin(include_columns)).any(axis=1)]
+
+# Display the filtered DataFrame
+st.subheader('Filtered DataFrame')
+st.write(filtered_df)