import pandas as pd

# Create the first dataframe
data = {
    'DATE': [20250101, 20250101, 20250101, 20250101,
             20250201, 20250201, 20250201, 20250201,
             20250301, 20250301, 20250301, 20250301],
    'TRAN_ID': [1, 2, 3, 4, 1, 2, 3, 4, 1, 2, 3, 4],
    'COST': [50, 30, 3, 2.5, 65, 0, 3.9, 4, 95, 70, 5.7, 6.5]
}

df1 = pd.DataFrame(data)

# Create the second dataframe
trans_desc = {
    'TRAN_ID': [1, 2, 3, 4],
    'DESCRIPTION': ['SALE PRICE', 'COST', 'TAX', 'FREIGHT']
}

df2 = pd.DataFrame(trans_desc)

# Merge dataframes
merged_df = pd.merge(df1, df2, on='TRAN_ID')

# Pivot to get each description as column
pivot_df = merged_df.pivot(index='DATE', columns='DESCRIPTION', values='COST').reset_index()

# Compute profit = SALE PRICE - COST - TAX - FREIGHT
pivot_df['PROFIT'] = pivot_df['SALE PRICE'] - pivot_df['COST'] - pivot_df['TAX'] - pivot_df['FREIGHT']

import caas_jupyter_tools
caas_jupyter_tools.display_dataframe_to_user("Profit by Date", pivot_df)