How to run a method on a field of a pandas DataFrame and set the result to another field

pandas_dataframe_parallel.py

def process_split(df: pd.DataFrame, f: types.FunctionType, in_key: str, out_key: str):
    """Process each chunk of a DataFrame, apply a funtion on an in_key and store it in an out_key"""
    
    rows = []
    for index, row in df.iterrows():
        result = f(row[in_key])
        row[out_key] = result
        rows.append(row)
    
    df_out = pd.DataFrame(rows)
    df_out = df_out.reindex().sort_index()
    return df_out


def parallel_apply(
    df: pd.DataFrame,
    f: types.FunctionType,
    in_key: str,
    out_key: str,
    n_cores: int=cpu_count
):
    """Apply a function to a DataFrame on an in_key and store it in an out_key with n_cores proceses"""
    
    n_cores = int(cpu_count() / 2) if callable(cpu_count) else cpu_count
    
    df_split = np.array_split(df, n_cores)
    pool = Pool(n_cores)
    
    df_out = pd.concat(
        pool.starmap(
            process_split,
            repeat(
                [df_split, f, in_key, out_key],
                times=n_cores
            ),
        )
    )
    df_out = df_out.reindex().sort_index()
    
    pool.close()
    pool.join()
    
    return df_out