TypeError: 'int' object is not subscriptable. Надо высчитать самую высокую зарплату среди Female и Male

import numpy as np
 
def salary_info(data, gender=None):
    print('This statisctics are for Female and Male:')
    lst_1 = []
    for index in range(len(data)):
        if data[index][1] == 'Female':
            
            lst_1.append(index[3])
            salary = np.array(lst_1)
            max_salary = salary.max()
            print('Max salary:', max_salary)
            
        else:
            lst_1.append(index[3])
            salary = np.array(lst_1)
            max_salary = salary.max()
            print('Max salary:', max_salary)
 
 
salary_info(filt_data, gender="Female")

import pandas as pd 
import numpy as np
 
data = [['15624510', 'Male', '19', '19000', '0'], 
        ['15810944', 'Male', '35', '20000', '0'], 
        ['15668575', 'Female', '26', '43000', '0'], 
        ['15603246', 'Female', '27', '57000', '0'], 
        ['15804002', 'Male', '19', '76000', '0'], 
        ['15728773', 'Male', '27', '58000', '0'], 
        ['15598044', 'Female', '27', '84000', '0'], 
        ['15694829', 'Female', '32', '150000', '1'], 
        ['15600575', 'Male', '25', '33000', '0'], 
        ['15727311', 'Female', '35', '65000', '0'], 
        ['15570769', 'Female', '26', '80000', '0'], 
        ['15606274', 'Female', '26', '52000', '0'], 
        ['15746139', 'Male', '20', '86000', '0']]
 
df = pd.DataFrame(data, columns = ['id', 'gender', 'age', 'salary', 'tmp'])
df[['age','salary']] = df[['age','salary']].astype('int32',errors='ignore')
print(df)
 
max_salary_gender = df.groupby('gender')['salary'].max().to_dict()
print(max_salary_gender)

df = df.apply(pd.to_numeric,errors='ignore')

def salary_info(data, gender=None):
    print(f'This statisctics are for {gender}:')
    lst_1, lst_2 = [], []
    for index in range(len(data)):
        if data[index][1] == gender:
            lst_1.append(int(data[index][3]))
    max_salary = max(lst_1)
    print(f'Max salary: {max_salary}')
 
 
filt_data = [['15624510', 'Male', '19', '19000', '0'], 
        ['15810944', 'Male', '35', '20000', '0'], 
        ['15668575', 'Female', '26', '43000', '0'], 
        ['15603246', 'Female', '27', '57000', '0'], 
        ['15804002', 'Male', '19', '76000', '0'], 
        ['15728773', 'Male', '27', '58000', '0'], 
        ['15598044', 'Female', '27', '84000', '0'], 
        ['15694829', 'Female', '32', '150000', '1'], 
        ['15600575', 'Male', '25', '33000', '0'], 
        ['15727311', 'Female', '35', '65000', '0'], 
        ['15570769', 'Female', '26', '80000', '0'], 
        ['15606274', 'Female', '26', '52000', '0'], 
        ['15746139', 'Male', '20', '86000', '0']]
 
salary_info(filt_data, gender="Female")