Researcher at the Czech Academy of Sciences.

• Banach spaces and their operators; geometry of Banach spaces;
• Ideals and representations of operator algebras and, more generally, Banach algebras;
• Applied Probability, Financial markets, Python modelling.

import pandas as pd

Assuming df1 and df2 are your existing DataFrames

Merging df1 and df2 on GFCID and period

df_merged = pd.merge(df1, df2[['GFCID', 'period']], on=['GFCID', 'period'], how='left', indicator=True)

Adding the def_flag column based on the conditions

df1['def_flag'] = ( (df_merged['_merge'] == 'both') | # Condition 1: GFCID and period values match (df1['ORR'].isin(["9", "9-", "10"])) | # Condition 2a: ORR is in the list ["9", "9-", "10"] (df1['Baseline_ORR_orig'].isin(["9", "9-", "10"])) # Condition 2b: Baseline_ORR_orig is in the list ["9", "9-", "10"] ).astype(int)

Drop the temporary '_merge' column if needed

df_merged.drop(columns=['_merge'], inplace=True)

The final DataFrame df1 now contains the 'def_flag' column