Chapter 6: Introduction to NumPy

NCERT solutions Introduction to NumPy

1. What is NumPy ? How to install it?

Numpy stands for Numberical Python . It is a package for data analysis and scientific computing with Python. Numpy can be installed by typing the commond : pip install Numpy

2. What is an array and how is it different from a list? What is the name of the built-in array class in NumPy?

Array is a data type used to store multiple values using a single identifier (variable name ) . An array constains an ordered collection of data elements where each element is of the same type and can be referenced by its index ( position ) ndarray is the name of the built-in array class in Numpy .

3. What do you understand by rank of an ndarray?

The number of dimensions or axes of the array is called rank of the array.

4. Create the following NumPy arrays: a) A 1-D array called zeros having 10 elements and all the elements are set to zero.

zeros = np.zeros((1,10))

b) A 1-D array called vowels having the elements ‘a’,‘e’, ‘i’, ‘o’ and ‘u’

vowels = np.array([‘a’,’e’,’i’,’o’,’u’])

c) A 2-D array called ones having 2 rows and 5 columns and all the elements are set to 1 and dtype as int.

ones = np.ones((2,5),dtype=int)

d) Use nested Python lists to create a 2-D array calledmyarray1 having 3 rows and 3 columns and store the following data:  2.7,     -2,     -19  0,       3.4,    99.9  10.6,   0,       13

myarray1 = np.array([[2.7, -2, -19],[0, 3.4, 99.9],[10.6, 0, 13]])

e) A 2-D array called myarray2 using arange()having 3 rows and 5 columns with start value = 4, step size 4 and dtype as float.

myarray2 = np.array(np.arange(4,61,4),dtype=float).reshape(3,5)

NCERT solutions Introduction to NumPy 5. Using the arrays created in Question 4 above, write NumPy commands for the following: a) Find the dimensions, shape, size, data type of the items and itemsize of arrays zeros, vowels, ones, myarray1 and myarray2.

zeros.shape vowels.shape ones.shape myarray1.shape myarray2.shape zeros.size vowels.size ones.size myarray1.size myarray2.size zeros.dtype vowels.dtype ones.dtype myarray1.dtype myarray2.dtype zeros.itemsize vowels.itemsize ones.itemsize myarray1.itemsize myarray2.itemsize

b) Reshape the array ones to have all the 10 elements in a single row

ones.reshape(1,10)

c) Display the 2nd and 3rd element of the array vowels.

print(vowal[1],vowel[2])

d) Display all elements in the 2nd and 3rd row of the array myarray1.

print(myarray1[1:3,])

e) Display the elements in the 1st and 2nd column of the array myarray1.

print(myarray1[0:3,0:2])

f) Display the elements in the 1st column of the 2nd and 3rd row of the array myarray1

print((myarray1[1:3,0:3]).reshape(1,6))

g) Reverse the array of vowels.

print(vowal[::-1]

6. Using the arrays created in Question 4 above, write  NumPy commands for the following: a) Divide all elements of array ones by 3.

ones/1

b) Add the arrays myarray1 and myarray2.

myarray1 + myarray2

c) Subtract myarray1 from myarray2 and store the result in a new array.

newarray = myarray2 – myarray1

d) Multiply myarray1 and myarray2 elementwise.

myarray1 * myarray2

e) Do the matrix multiplication of myarray1 and myarray2 and store the result in a new array  myarray3.

myarray3 = myarray1 @ myarray2

f) Divide myarray1 by myarray2.

myarray1 / myarray2

g) Find the cube of all elements of myarray1 and divide the resulting array by 2.

myarray1 **3/2

h) Find the square root of all elements of myarray2 and divide the resulting array by 2. The result  should be rounded to two places of decimals.

np.around(myarray**(1/2)/2,2)

7. Using the arrays created in Question 4 above, write NumPy commands for the following: a) Find the transpose of ones and myarray2.

ones.transpose() myarray2.transpose

b) Sort the array vowels in reverse.

(np.sort(vowels))[::-1)

c) Sort the array myarray1 such that it brings the lowest value of the column in the first row and so on.

myarray1.sort(axis=0)

8. Using the arrays created in Question 4 above, write NumPy commands for the following: a) Use NumPy. split() to split the array myarray2  into 5 arrays columnwise. Store your resulting arrays in myarray2A, myarray2B, myarray2C, myarray2D and myarray2E. Print the arrays myarray2A, myarray2B, myarray2C, myarray2D and myarray2E.

myarray2A, myarray2B, myarray2C, myarray2D, myarray2E = np.array_split(myarray2,5,axis=1)

c) Concatenate the arrays myarray2A, myarray2B and myarray2C into an array having 3 rows and 3  columns.

(np.array([myarray2A, myarray2B, myarray2C])).reshape(3,3)

9. Create a 2-D array called myarray4 using arange()  having 14 rows and 3 columns with start value = -1,  step size 0.25 having. Split this array row wise into 3  equal parts and print the result.

myarray4 = np.arrange(-1,9.5,0.25) a1,a2,a3 = np.array_split(myarray4,3,axis=0)

NCERT solutions Introduction to NumPy 10. Using the myarray4 created in the above questions,  write commands for the following:  a) Find the sum of all elements.

myarray4.sum()

b) Find the sum of all elements row wise.

myarray4.sum(axis=1)

c) Find the sum of all elements column wise.

myarray4.sum(aixis=0)

d) Find the max of all elements.

myarray4.max()

e) Find the min of all elements in each row.

myarray4.min()

f) Find the mean of all elements in each row.

myarray4.mean(axis=1)

g) Find the standard deviation column wise.

myarray4..std(axis=0)

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