pandas_find_max_in_group.py

def find_max_in_group(df, group_col, val_col, tie_for_first=False):
    # Decide ranking method
    if tie_for_first:
        rank_method = 'min'
    else:
        rank_method = 'first'
    # Add rank number for each group
    df["rank"] = df.groupby(group_col)[val_col].rank(method=rank_method, ascending=False)
    # Only return rank == 1
    return df[df['rank'] == 1].drop(['rank'], axis=1)