<jupyter_start><jupyter_text><jupyter_code># Importing libraries
import pandas as pd
import numpy as np
import random
# Prevewing the dataset
url = 'http://bit.ly/MedicalCitiesIncomeDataset'
df = pd.read_csv(url)
df.head()
# Displaying the size of the data
df.shape
# Selecting a sample from the data
df1 = df.sample(n = 30, replace="False")
print(df1)<jupyter_output>Number             City  Gender  Age    Income Illness
41483    41484    New York City  Female   28   96787.0      No
100946  100947      Los Angeles    Male   51  103150.0      No
70444    70445      Los Angeles    Male   55  100448.0      No
10581    10582           Dallas    Male   65   51065.0      No
50373    50374    New York City    Male   61  105588.0      No
62143    62144    New York City    Male   55  102447.0      No
67451    67452    New York City    Male   36  107633.0      No
44674    44675    New York City    Male   36  124561.0      No
95185    95186      Los Angeles    Male   64  109195.0      No
118719  118720           Boston    Male   30  106494.0      No
141285  141286           Austin    Male   41   96061.0      No
118577  118578           Boston    Male   58  105496.0     Yes
13080    13081           Dallas  Female   40   58899.0      No
49750    49751    New York City    Male   41  104822.0      No
95790    95791      Los Angeles  Female   28   91380.0 [...]
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