Blogs - Page 59 Of 116

Convert an array of float datatype to integer

In this python numpy program, we will convert an array of float datatype to integer.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Convert an array having values as float datatype to an integer using astype(int).
Print the output.

				
					import numpy as np
x = np.array([[6.7, 5.2],[9.4, 2.7]])
print("Float array: \n",x)
print("Integer array: \n",x.astype(int))

Output :

				
					Float array: 
 [[6.7 5.2]
 [9.4 2.7]]
Integer array: 
 [[6 5]
 [9 2]]

access an array by column.

add an extra column to an array.

Program to access an array by column using NumPy

In this python numpy program, we will access an array by column using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Access an array by column using indexing (i.e. array[row, column] ) and logic.
Print the output.

				
					import numpy as np
x = np.array([[4,8,0],[2,0,6]])
print("1st column: \n",x[:,0])
print("2nd column: \n",x[:,1])
print("3rd column: \n",x[:,2])

Output :

				
					1st column: 
 [4 2]
2nd column: 
 [8 0]
3rd column: 
 [0 6]

print squares of all the elements of an array.

convert an array of float values to an array of integer values.

Print squares of all the elements of an array using NumPy.

In this python numpy program, we will print squares of all the elements of an array using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Use np.square() to get the squares of all the elements in the given array.
Print the output.

				
					import numpy as np 
x = np.array([2,6,3,1])

print("Sqaure of every element in the arrary: ",np.square(x))

Output :

				
					Sqaure of every element in the arrary:  [ 4 36  9  1]

print every element of an array.

access an array by column.

Print every element of an array using NumPy

In this python numpy program, we will print every element of an array using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Use for loop with np.nditer() to print every element of the given array.
Print the output.

				
					import numpy as np
x = np.array([[4,8,0],[2,0,6]])

for ele in np.nditer(x):
    print(ele,end=' ')

Output :

				
					4 8 0 2 0 6

make an array immutable i.e. read-only.

print squares of all the elements of an array.

Program to make an array immutable using NumPy

In this python numpy program, we will make an array immutable using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Make an array immutable i.e. read-only by setting flags.writeable as False.
When we try to change any value of the array it will show the error as
```
ValueError: assignment destination is read-only.
```

				
					import numpy as np
x = np.array([[5, 3],[7, 4]])
x.flags.writeable = False
x[0,1] = 0

Output :

				
					ValueError                                Traceback (most recent call last)
<ipython-input-6-6fe1d7a57604> in <module>
      3 x = np.array([[5, 3],[7, 4]])
      4 x.flags.writeable = False
----> 5 x[0,1] = 0

ValueError: assignment destination is read-only

find the median of the matrix along the column.

print every element of an array.

Median of the matrix along the column using NumPy

In this python numpy program, we will find the median of the matrix along the column using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Find the median of the matrix along the column using np.median() and set the axis equal to 1.
Print the output.

				
					import numpy as np
x = np.array([[5, 3],[7, 4]])
print("Median of array along column:",np.median(x,axis=1))

Output :

				
					Median of array along column: [4.  5.5]

find the median of the matrix along the rows.

make an array immutable i.e. read-only.

Median of the matrix along the rows using NumPy

In this python numpy program, we will find the median of the matrix along the rows using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Find the median of the matrix along the rows using np.median() and set the axis equal to 0.
Print the output.

				
					import numpy as np
x = np.array([[5, 3],[7, 4]])
print("Median of array along row:",np.median(x,axis=0))

Output :

				
					Median of array along row: [6.  3.5]

find the median of the matrix.

find the median of the matrix along the column.

Find the median of the matrix using NumPy.

In this python numpy program, we will find the median of the matrix using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Find the median of the matrix using np.median().
Print the output.

				
					import numpy as np
x = np.array([[5, 3],[7, 4]])
print("Median of array:",np.median(x))

Output :

				
					Median of array: 4.5

get the number of nonzero elements in an array.

find the median of the matrix along the rows.

Get the number of nonzero elements in an array using NumPy

In this python numpy program, we will get the number of nonzero elements in an array using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Get the number of nonzero elements in an array using np.count_nonzero().
Print the output.

				
					import numpy as np
x = np.array([[4, 8, 0],[2, 0, 6]])
print("Number of non-zero elements: ",np.count_nonzero(x))

Output :

				
					Number of non-zero elements:  4

split an array of 10 elements into 3 arrays, each of which has 2, 3, and 5 elements.

find the median of the matrix.

Split an array of 10 elements into 3 arrays using NumPy.

In this python numpy program, we will split an array of 10 elements into 3 arrays using NumPy.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Split an array of 10 elements into 3 arrays, each of which has 2, 3, and 5 elements using np.split().
Print the output.

				
					import numpy as np
x = np.arange(1, 11)
print("Original array:",x)
print("After splitting:")
print(np.split(x, [2, 5]))

Output :

				
					Original array: [ 1  2  3  4  5  6  7  8  9 10]
After splitting:
[array([1, 2]), array([3, 4, 5]), array([ 6,  7,  8,  9, 10])]

convert 1-D arrays as columns into a 2-D array.

get the number of nonzero elements in an array.