Numpy Excercise.ipynb

Kernel: Python 3

Write a NumPy program to test whether none of the elements of a given array is zero.

import numpy as np
x = np.array([1, 2, 3, 4])
print("Original array:",x)
print("Test if none of the elements of the said array is zero\n:",np.all(x))
y = np.array([0, 1, 2, 3])
print("Original array:",y)
print("Test if none of the elements of the said array is zero:\n",np.all(y))

Original array: [1 2 3 4]
Test if none of the elements of the said array is zero
: True
Original array: [0 1 2 3]
Test if none of the elements of the said array is zero:
 False

Write a NumPy program to create an array of 5 zeros, 5 ones, 5 fives.

import numpy as np
a1=np.zeros(5)
a2=np.ones(5)
a3=np.ones(5)*5
np.concatenate((a1,a2,a3), axis=0)

array([0., 0., 0., 0., 0., 1., 1., 1., 1., 1., 5., 5., 5., 5., 5.])

Write a NumPy program to generate an array of 15 random numbers from a standard normal distribution

import numpy as np
rand_num = np.random.normal(0,1,15)
print("15 random numbers from a standard normal distribution:")
print(rand_num)

Write a NumPy program to create a vector with values ranging from 10 to 40 and print all values except the first and last.

import numpy as np
v = np.arange(10,40)
print("Original vector:")
print(v)
print(" \nExcluding first and last")
print(v[1:-1])

Write a NumPy program to create a vector with values from 1 to 15 and change the sign of the numbers in the range from 10 to 15.

import numpy as np
x = np.arange(15)
print("Original vector:")
print(x)
print("After changing the sign of the numbers in the range from 9 to 15:")
x[(x >= 10) & (x <= 15)] *= -1
print(x)

Write a NumPy program to create a 3x4 matrix filled with values from 10 to 21

import numpy as np
a= np.arange(10,22).reshape((3, 4))
print(a)

[[10 11 12 13]
 [14 15 16 17]
 [18 19 20 21]]

Write a NumPy program to compute the inner product of two given vectors

import numpy as np
x = np.array([4, 5])
y = np.array([7, 10])
print("Original vectors:")
print(x)
print(y)
print("Inner product of said vectors:")
print(np.dot(x, y))

Write a NumPy program to create a structured array from given student name, height, class and their data types. Now sort the array on height.

import numpy as np
data_type = [('name', 'S15'), ('class', int), ('height', float)]
students_details = [('James', 5, 48.5), ('Nail', 6, 52.5),('Paul', 5, 42.10), ('Pit', 5, 40.11)]
# create a structured array
students = np.array(students_details, dtype=data_type)   
print("Original array:")
print(students)
print("Sort by height")
print(np.sort(students, order='height'))    

Write a NumPy program to add, subtract, multiply, divide arguments element-wise.

import numpy as np
print("Add:")
print(np.add(1.0, 4.0))
print("Subtract:")
print(np.subtract(1.0, 4.0))
print("Multiply:")
print(np.multiply(1.0, 4.0))
print("Divide:")
print(np.divide(1.0, 4.0))

Write a NumPy program to get the minimum and maximum value of a given array along the second axis.

import numpy as np
x = np.arange(4).reshape((2, 2))
print("\nOriginal array:")
print(x)
print("\nMaximum value along the second axis:")
print(np.amax(x, 1))
print("Minimum value along the second axis:")
print(np.amin(x, 1))

Write a NumPy program to display all the dates for the month of May, 2019

import numpy as np
print("May, 2019")
print(np.arange('2019-05', '2019-06', dtype='datetime64[D]'))

Write a NumPy program to capitalize the first letter, lowercase, uppercase, swapcase, title-case of all the elements of a given array

import numpy as np
x = np.array(['ml', 'PYTHON', 'Data Science', 'Numpy'], dtype=np.str)
print("Original Array:")
print(x)
capitalized_case = np.char.capitalize(x)
lowered_case = np.char.lower(x)
uppered_case = np.char.upper(x)
swapcased_case = np.char.swapcase(x)
titlecased_case = np.char.title(x)
print("\nCapitalized: ", capitalized_case)
print("Lowered: ", lowered_case)
print("Uppered: ", uppered_case)
print("Swapcased: ", swapcased_case)
print("Titlecased: ", titlecased_case)