Load the sample data.

   Create an array.

   Do indexing and slicing of an array using appropriate procedures.

   Print the results.

#import libraries
import numpy as np
import pandas as pd

#load the sample data from csv file
data = pd.read_csv(‘/home/soft50/soft50/Sathish/practice/iris.csv’)

#Make it as a data frame
df = pd.DataFrame(data)

#feature selection
X = np.array(df.iloc[:,0:4])
print(“Sample data\n”)
for i in range(20):
print(X[i])
print(“\n”)

#Subsetting of an array
print(“Subsetting an array\n”)
print(X[2])
print(X[2,2])
print(“\n”)

#Slicing of an array
print(“Slicing an array\n”)
print(X[0:2],”\n”)
print(X[0:2,3])
print(“\n”)

#Boolean indexing of an array
print(“Boolean indexing\n”)
print(X[X<3])
print(“\n”)

#Fancy indexing of an array
print(“Fancy Indexing an array\n”)
print(X[[1, 0, 1, 0]][:,[0,1,2,0]])