Reading a CSV file and translate into dataframe

Below, a script is provided that reads a CSV file and translate the outcome into a dataframe:

import csv
import pandas as pd

with open(r"C:\Users\tomva\SynologyDrive\python\pandas\Incomplete\banking.csv","r") as csv_file:
    csv_reader = csv.reader(csv_file, delimiter = ',')
    print(type(csv_reader))
    df = pd.DataFrame()  
    i = 0
    for row in csv_reader:
        if i == 0:
            cols = row
        if i > 0:
            for j in range(len(row)):
                df.loc[i, j] = row[j]
        if i%1000 == 0:
            print(i)
        i = i + 1
    print(cols)
    df = df.rename(columns={0: 'age', 1: 'job', 2: 'marital', 3: 'education', 4: 'default', 5: 'housing', 6: 'loan', 7: 'contact', 8: 'month', 9: 'day_of_week', 10: 'duration', 11: 'campaign', 12: 'pdays', 13: 'previous', 14: 'poutcome', 15: 'emp_var_rate', 16: 'cons_price_idx', 17: 'cons_conf_idx', 18: 'euribor3m', 19: 'nr_employed', 20: 'y'})    
    df.info()
print('********* Klaar ********************')