.iloc selects data only by integer location:

import pandas as pd

df = pd.DataFrame({'Age': [30, 20, 22, 40, 32, 28, 39],
                   'Color': ['Blue', 'Green', 'Red', 'White', 'Gray', 'Black',
                             'Red'],
                   'Food': ['Steak', 'Lamb', 'Mango', 'Apple', 'Cheese',
                            'Melon', 'Beans'],
                   'Height': [165, 70, 120, 80, 180, 172, 150],
                   'Score': [4.6, 8.3, 9.0, 3.3, 1.8, 9.5, 2.2],
                   'State': ['NY', 'TX', 'FL', 'AL', 'AK', 'TX', 'TX']
                   },
                  index=['Jane', 'Nick', 'Aaron', 'Penelope', 'Dean',
                         'Christina', 'Cornelia'])

print("\n -- Selecting a single row with .iloc with an integer -- \n")
print(df.iloc[4])

print("\n -- Selecting multiple rows with .iloc with a list of integers -- \n")
print(df.iloc[[2, -2]])

print("\n -- Selecting multiple rows with .iloc with slice notation -- \n")
print(df.iloc[:5:3])

C:\python\pandas examples>python example13.py
 
 -- Selecting a single row with .iloc with an integer --
 
Age           32
Color       Gray
Food      Cheese
Height       180
Score        1.8
State         AK
Name: Dean, dtype: object
 
 -- Selecting multiple rows with .iloc with a list of integers --
 
           Age  Color   Food  Height  Score State
Aaron       22    Red  Mango     120    9.0    FL
Christina   28  Black  Melon     172    9.5    TX
 
 -- Selecting multiple rows with .iloc with slice notation --
 
          Age  Color   Food  Height  Score State
Jane       30   Blue  Steak     165    4.6    NY
Penelope   40  White  Apple      80    3.3    AL
 
C:\python\pandas examples>