Python Numpy Problems Archives - Page 3 Of 10

Program to calculate the product of a NumPy array

In this python numpy program, we will calculate the product of a NumPy array.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Calculate the product of the given array using prod().
Print the output.

				
					import numpy as np
x = np.array([3, 5, 1])

print("Product of the elements in the given array: ",x.prod())

Output :

				
					Product of the elements in the given array:  15

check whether an array is empty.

convert an array into a CSV file.

Program to check whether the NumPy array is empty

In this python numpy program, we will check whether the NumPy array is empty.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Get the size of the array (i.e. total number of elements) using size.
Determine whether the given array is empty or not using an if-else statement.
If the size of the array is 0 then the array is empty else the array is not empty.
Print the respective output.

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

if x.size == 0:
    print("Array is empty")
else:
    print("Array is not empty")

Output :

				
					Array is not empty

count the frequency of unique values.

calculate the product of an array.

Get the count the frequency of unique values from the NumPy array

In this python numpy program, we will count the frequency of unique values from the NumPy array.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Get the unique values and their frequency from the array using np.unique(array,return_counts=True).
Print the output.

				
					import numpy as np
x = np.array([8, 6, 7, 0, 7, 8, 6, 6])

unique, count = np.unique(x, return_counts=True)
print("Frequency of unique values in the given array:")
print(np.asarray((unique, count)))

Output :

				
					Frequency of unique values in the given array:
[[0 6 7 8]
 [1 3 2 2]]

get the magnitude of a vector.

check whether an array is empty.

Program to get the magnitude of a NumPy vector

In this python numpy program, we will get the magnitude of a NumPy vector.

Steps to solve the program

Import the numpy library as np.
Create a vector using np.array().
Get the magnitude of the vector using np.linalg.norm().
Print the output.

				
					import numpy as np
x = np.array([3, 5, 1])

print("Magnitude of the given vector: ",np.linalg.norm(x))

Output :

				
					Magnitude of the given vector:  5.916079783099616

remove all rows in a NumPy array that contain non-numeric values.

count the frequency of unique values.

Remove all rows that contain non-numeric values from an NumPy array

In this python numpy program, we will remove all rows that contain non-numeric values from a NumPy array.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Remove all rows that contain non-numeric values from the array using array[~np.isnan(array).any(axis=1)].
Print the output.

				
					import numpy as np
x = np.array([[4,8, np.nan],[2,4,6]])
print("Old: \n",x)

print("New: \n",x[~np.isnan(x).any(axis=1)])

Output :

				
					Old: 
 [[ 4.  8. nan]
 [ 2.  4.  6.]]
New: 
 [[2. 4. 6.]]

replace the negative values in an array with 1.

get the magnitude of a vector.

Replace the negative values in an NumPy array

In this python numpy program, we will replace the negative values in an NumPy array.

Steps to solve the program

Import the numpy library as np.
Create an array using np.array().
Replace the negative values in the given array with 1 using indexing and logic.
Print the output.

				
					import numpy as np
x = np.array([[4,8,-5],[2,-9,6]])
print("Old: \n",x)

x[x<0] = 1
print("New: \n",x)

Output :

				
					Old: 
 [[ 4  8 -5]
 [ 2 -9  6]]
New: 
 [[4 8 1]
 [2 1 6]]

add an extra column to an array.

remove all rows in a NumPy array that contain non-numeric values.

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.