# NumPy: Array Object Exercises, Practice, Solution

## NumPy Array Object [205 exercises with solution]

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**1.** Write a NumPy program to print the NumPy version in your system. Go to the editor

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**2.** Write a NumPy program to convert a list of numeric value into a one-dimensional NumPy array. Go to the editor

Expected Output:

Original List: [12.23, 13.32, 100, 36.32]

One-dimensional NumPy array: [ 12.23 13.32 100. 36.32]

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**3.**Write a NumPy program to create a 3x3 matrix with values ranging from 2 to 10. Go to the editor

Expected Output:

[[ 2 3 4]

[ 5 6 7]

[ 8 9 10]]

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**4. **Write a NumPy program to create a null vector of size 10 and update sixth value to 11.Go to the editor

[ 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.]

Update sixth value to 11

[ 0. 0. 0. 0. 0. 0. 11. 0. 0. 0.]

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**5.** Write a NumPy program to create an array with values ranging from 12 to 38.Go to the editor

Expected Output:

[12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
37]

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**6.** Write a NumPy program to reverse an array (first element becomes last). Go to the editor

Original array:

[12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36
37]

Reverse array:

[37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13
12]

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**7.** Write a NumPy program to convert an array to a float type. Go to the editor

Sample output:

Original array

[1, 2, 3, 4]

Array converted to a float type:

[ 1. 2. 3. 4.]

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**8. ** Write a NumPy program to create a 2d array with 1 on the border and 0 inside. Go to the editor

Expected Output:

Original array:

[[ 1. 1. 1. 1. 1.]

...................

[ 1. 1. 1. 1. 1.]]

1 on the border and 0 inside in the array

[[ 1. 1. 1. 1. 1.]

...................

[ 1. 1. 1. 1. 1.]]

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**9. ** Write a NumPy program to add a border (filled with 0's) around an existing array. Go to the editor

Expected Output:

Original array:

[[ 1. 1. 1.]

[ 1. 1. 1.]

[ 1. 1. 1.]]

1 on the border and 0 inside in the array

[[ 0. 0. 0. 0. 0.]

...........

[ 0. 0. 0. 0. 0.]]

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**10. ** Write a NumPy program to create a 8x8 matrix and fill it with a checkerboard pattern. Go to the editor

Checkerboard pattern:

[[0 1 0 1 0 1 0 1]

..........

[0 1 0 1 0 1 0 1]

[1 0 1 0 1 0 1 0]]

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**11. ** Write a NumPy program to convert a list and tuple into arrays. Go to the editor

List to array:

[1 2 3 4 5 6 7 8]

Tuple to array:

[[8 4 6]

[1 2 3]]

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**12. ** Write a NumPy program to append values to the end of an array. Go to the editor

Expected Output:

Original array:

[10, 20, 30]

After append values to the end of the array:

[10 20 30 40 50 60 70 80 90]

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**13. ** Write a NumPy program to create an empty and a full array. Go to the editor

Expected Output:

[ 6.93270651e-310 1.59262180e-316 6.93270559e-310 6.93270665e-310]

[ 6.93270667e-310 6.93270671e-310 6.93270668e-310 6.93270483e-310]

[ 6.93270668e-310 6.93270671e-310 6.93270370e-310 6.93270488e-310]]

[[6 6 6]

[6 6 6]

[6 6 6]]

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**14. ** Write a NumPy program to convert the values of Centigrade degrees into Fahrenheit degrees. Centigrade values are stored into a NumPy array. Go to the editor

Sample Array [0, 12, 45.21 ,34, 99.91]

Expected Output:

Values in Fahrenheit degrees:

[ 0. 12. 45.21 34. 99.91]

Values in Centigrade degrees:

[-17.77777778 -11.11111111 7.33888889 1.11111111 37.72777778]

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**15.** Write a NumPy program to find the real and imaginary parts of an array of complex numbers. Go to the editor

Expected Output:

Original array [ 1.00000000+0.j 0.70710678+0.70710678j]

Real part of the array:

[ 1. 0.70710678]

Imaginary part of the array:

[ 0. 0.70710678]

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**16.** Write a NumPy program to find the number of elements of an array, length of one array element in bytes and total bytes consumed by the elements. Go to the editor

Expected Output:

Size of the array: 3

Length of one array element in bytes: 8

Total bytes consumed by the elements of the array: 24

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**17.** Write a NumPy program to test whether each element of a 1-D array is also present in a second array. Go to the editor

Expected Output:

Array1: [ 0 10 20 40 60]

Array2: [0, 40]

Compare each element of array1 and array2

[ True False False True False]

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**18.** Write a NumPy program to find common values between two arrays. Go to the editor

Expected Output:

Array1: [ 0 10 20 40 60]

Array2: [10, 30, 40]

Common values between two arrays:

[10 40]

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**19.** Write a NumPy program to get the unique elements of an array. Go to the editor

Expected Output:

Original array:

[10 10 20 20 30 30]

Unique elements of the above array:

[10 20 30]

Original array:

[[1 1]

[2 3]]

Unique elements of the above array:

[1 2 3]

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**20.** Write a NumPy program to find the set difference of two arrays. The set difference will return the sorted, unique values in array1 that are not in array2. Go to the editor

Expected Output:

Array1: [ 0 10 20 40 60 80]

Array2: [10, 30, 40, 50, 70, 90]

Set difference between two arrays:

[ 0 20 60 80]

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**21.** Write a NumPy program to find the set exclusive-or of two arrays. Set exclusive-or will return the sorted, unique values that are in only one (not both) of the input arrays. Go to the editor

Array1: [ 0 10 20 40 60 80]

Array2: [10, 30, 40, 50, 70]

Unique values that are in only one (not both) of the input arrays:

[ 0 20 30 50 60 70 80]

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**22.** Write a NumPy program to find the union of two arrays. Union will return the unique, sorted array of values that are in either of the two input arrays. Go to the editor

Array1: [ 0 10 20 40 60 80]

Array2: [10, 30, 40, 50, 70]

Unique sorted array of values that are in either of the two input arrays:

[ 0 10 20 30 40 50 60 70 80]

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**23.** Write a NumPy program to test whether all elements in an array evaluate to True. Go to the editor

Note: 0 evaluates to False in NumPy.

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**24.** Write a NumPy program to test whether any array element along a given axis evaluates to True. Go to the editor

Note: 0 evaluates to False in NumPy.

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**25.** Write a NumPy program to construct an array by repeating. Go to the editor

Sample array: [1, 2, 3, 4]

Expected Output:

Original array

[1, 2, 3, 4]

Repeating 2 times

[1 2 3 4 1 2 3 4]

Repeating 3 times

[1 2 3 4 1 2 3 4 1 2 3 4]

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**26.** Write a NumPy program to repeat elements of an array. Go to the editor

Expected Output:

[3 3 3 3]

[1 1 2 2 3 3 4 4]

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**27.** Write a NumPy program to find the indices of the maximum and minimum values along the given axis of an array. Go to the editor

Original array: [1 2 3 4 5 6]

Maximum Values: 5

Minimum Values: 0

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**28.** Write a NumPy program compare two given arrays. Go to the editor

Array a: [1 2]

Array b: [4 5]

a > b

[False False]

a >= b

[False False]

a < b

[ True True]

a <= b

[ True True]

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**29.** Write a NumPy program to sort an along the first, last axis of an array. Go to the editor

Sample array: [[2,5],[4,4]]

Expected Output:

Original array:

[[4 6]

[2 1]]

Sort along the first axis:

[[2 1]

[4 6]]

Sort along the last axis:

[[1 2]

[4 6]]

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**30.** Write a NumPy program to sort pairs of first name and last name return their indices. (first by last name, then by first name). Go to the editor

first_names = (Betsey, Shelley, Lanell, Genesis, Margery)

last_names = (Battle, Brien, Plotner, Stahl, Woolum)

Expected Output:

[1 3 2 4 0]

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**31.** Write a NumPy program to get the values and indices of the elements that are bigger than 10 in a given array. Go to the editor

Original array:

[[ 0 10 20]

[20 30 40]]

Values bigger than 10 = [20 20 30 40]

Their indices are (array([0, 1, 1, 1]), array([2, 0, 1, 2]))

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**32.** Write a NumPy program to save a NumPy array to a text file. Go to the editor

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**33.** Write a NumPy program to find the memory size of a NumPy array. Go to the editor

Expected Output:

128 bytes

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**34.** Write a NumPy program to create an array of ones and an array of zeros. Go to the editor

Expected Output:

Create an array of zeros

Default type is float

[[ 0. 0.]]

Type changes to int

[[0 0]]

Create an array of ones

Default type is float

[[ 1. 1.]]

Type changes to int

[[1 1]]

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**35.** Write a NumPy program to change the dimension of an array. Go to the editor

Expected Output:

6 rows and 0 columns

(6,)

(3, 3) -> 3 rows and 3 columns

[[1 2 3]

[4 5 6]

[7 8 9]]

Change array shape to (3, 3) -> 3 rows and 3 columns

[[1 2 3]

[4 5 6]

[7 8 9]]

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**36.** Write a NumPy program to create a contiguous flattened array. Go to the editor

Original array:

[[10 20 30]

[20 40 50]]

New flattened array:

[10 20 30 20 40 50]

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**37.** Write a NumPy program to create a 2-dimensional array of size 2 x 3 (composed of 4-byte integer elements), also print the shape, type and data type of the array. Go to the editor

Expected Output:

(2, 3)

int32

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**38.** Write a NumPy program to create a new shape to an array without changing its data. Go to the editor

Reshape 3x2:

[[1 2]

[3 4]

[5 6]]

Reshape 2x3:

[[1 2 3]

[4 5 6]]

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**39.** Write a NumPy program to change the data type of an array. Go to the editor

Expected Output:

[[ 2 4 6]

[ 6 8 10]]

Data type of the array x is: int32

New Type: float64

[[ 2. 4. 6.]

[ 6. 8. 10.]]

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**40.** Write a NumPy program to create a new array of 3*5, filled with 2. Go to the editor

Expected Output:

[[2 2 2 2 2]

[2 2 2 2 2]

[2 2 2 2 2]]

[[2 2 2 2 2]

[2 2 2 2 2]

[2 2 2 2 2]]

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**41.** Write a NumPy program to create an array of 10's with the same shape and type of a given array. Go to the editor

Sample array: x = np.arange(4, dtype=np.int64)

Expected Output:

[10 10 10 10]

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**42.** Write a NumPy program to create a 3-D array with ones on a diagonal and zeros elsewhere. Go to the editor

Expected Output:

[[ 1. 0. 0.]

[ 0. 1. 0.]

[ 0. 0. 1.]]

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**43.** Write a NumPy program to create a 2-D array whose diagonal equals [4, 5, 6, 8] and 0's elsewhere. Go to the editor

Expected Output:

[[4 0 0 0]

[0 5 0 0]

[0 0 6 0]

[0 0 0 8]]

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**44.** Write a NumPy program to create a 1-D array going from 0 to 50 and an array from 10 to 50. Go to the editor

Expected Output:

Array from 0 to 50:

[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49]

Array from 10 to 50:

[10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34

35 36 37 38 39 40 41 42 43 44 45 46 47 48 49]

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**45.** Write a NumPy program to Create a 1-D array of 30 evenly spaced elements between 2.5. and 6.5, inclusive. Go to the editor

Expected Output:

[ 2.5 2.63793103 2.77586207 2.9137931 3.05172414 3.18965517

.................

5.81034483 5.94827586 6.0862069 6.22413793 6.36206897 6.5 ]

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**46.** Write a NumPy program to create a 1-D array of 20 element spaced evenly on a log scale between 2. and 5., exclusive. Go to the editor

Expected Output:

[ 100. 141.25375446 199.5262315 281.83829313

......................

25118.8643151 35481.33892336 50118.72336273 70794.57843841]

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**47.** Write a NumPy program to create an array which looks like below array. Go to the editor

Expected Output:

[[ 0. 0. 0.]

...........

[ 1. 1. 1.]]

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**48.** Write a NumPy program to create an array which looks like below array. Go to the editor

Expected Output:

[[ 2 3 4]

[ 5 6 7]

[ 0 9 10]

[ 0 0 13]]

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**49.** Write a NumPy program to collapse a 3-D array into one dimension array. Go to the editor

Expected Output:

3-D array:

[[ 1. 0. 0.]

[ 0. 1. 0.]

[ 0. 0. 1.]]

One dimension array:

[ 1. 0. 0. 0. 1. 0. 0. 0. 1.]

Click me to see the sample solution

**50.** Write a NumPy program to find the 4th element of a specified array. Go to the editor

Expected Output:

[[ 2 4 6]

[ 6 8 10]]

Forth e1ement of the array:

6

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**51.** Write a NumPy program to interchange two axes of an array. Go to the editor

Sample array: [[1 2 3]]

Expected Output:

[[1]

[2]

[3]]

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**52.** Write a NumPy program to move axes of an array to new positions. Other axes remain in their original order. Go to the editor

Expected Output:

(3, 4, 2)

(4, 2, 3)

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**53.** Write a NumPy program to move the specified axis backwards, until it lies in a given position. Go to the editor

Move the following 3rd array axes to first position.

(2,3,4,5)

Sample Expected Output:

(2, 5, 3, 4)

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**54.** Write a NumPy program to convert specified inputs to arrays with at least one dimension. Go to the editor

Expected Output:

[ 12.]

[[ 0. 1. 2.]

[ 3. 4. 5.]]

[array([1]), array([3, 4])]

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**55.** Write a NumPy program to view inputs as arrays with at least two dimensions, three dimensions. Go to the editor

Expected Output:

View inputs as arrays with at least two dimensions:

[10]

[[ 0. 1.]

[ 2. 3.]]

View inputs as arrays with at least three dimensions:

[[[15]]]

[[[ 0.]

[ 1.]

[ 2.]]]

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**56.** Write a NumPy program to insert a new axis within a 2-D array. Go to the editor

2-D array of shape (3, 4).

Expected Output:

New shape will be will be (3, 1, 4).

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**57.** Write a NumPy program to remove single-dimensional entries from a specified shape. Go to the editor

Specified shape: (3, 1, 4)

Expected Output: (3, 4)

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**58.** Write a NumPy program to concatenate two 2-dimensional arrays. Go to the editor

Expected Output:

Sample arrays: ([[0, 1, 3], [5, 7, 9]], [[0, 2, 4], [6, 8, 10]]

Expected Output:

[[ 0 1 3 0 2 4]

[ 5 7 9 6 8 10]]

Click me to see the sample solution

**59.** Write a NumPy program to convert 1-D arrays as columns into a 2-D array. Go to the editor

Sample array: (10,20,30), (40,50,60)

Expected Output:

[[10 40]

[20 50]

[30 60]]

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**60.** Write a NumPy program to convert (in sequence depth wise (along third axis)) two 1-D arrays into a 2-D array. Go to the editor

Sample array: (10,20,30), (40,50,60)

Expected Output:

[[[10 40]]

[[20 50]]

[[30 60]]]

Click me to see the sample solution

**61.** Write a NumPy program to split an array of 14 elements into 3 arrays, each of which has 2, 4, and 8 elements in the original order. Go to the editor

Expected Output:

Original array: [ 1 2 3 4 5 6 7 8 9 10 11 12 13 14]

After splitting:

[array([1, 2]), array([3, 4, 5, 6]), array([ 7, 8, 9, 10, 11, 12, 13, 14])]

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**62.** Write a NumPy program to split of an array of shape 4x4 it into two arrays along the second axis. Go to the editor

Sample array :

[[ 0 1 2 3]

........

[12 13 14 15]]

Expected Output:

[array([[ 0, 1],

[ 4, 5],

[ 8, 9],

[12, 13]]), array([[ 2, 3],

[ 6, 7],

[10, 11],

[14, 15]]), array([], shape=(4, 0), dtype=int64)]

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**63.** Write a NumPy program to get the number of nonzero elements in an array. Go to the editor

Expected Output:

Original array:

[[ 0 10 20]

[20 30 40]]

Number of non zero elements in the above array:

5

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**64.** Write a NumPy program to create a 5x5 matrix with row values ranging from 0 to 4. Go to the editor

Original array:

[[ 0. 0. 0. 0. 0.]

.........

[ 0. 0. 0. 0. 0.]]

Row values ranging from 0 to 4.

[[ 0. 1. 2. 3. 4.]

..........

[ 0. 1. 2. 3. 4.]]

Click me to see the sample solution

**65.** Write a NumPy program to test whether specified values are present in an array. Go to the editor

Expected Output:

Original array:

[[ 1.12 2. 3.45]

[ 2.33 5.12 6. ]]

True

False

True

False

True

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**66.** Write a NumPy program to create a vector of size 10 with values ranging from 0 to 1, both excluded. Go to the editor

Expected Output:

[ 0.09090909 0.18181818 0.27272727 0.36363636 0.45454545 0.54545455

0.63636364 0.72727273 0.81818182 0.90909091]

Click me to see the sample solution

**67.** Write a NumPy program to make an array immutable (read-only). Go to the editor

Expected Output:

Test the array is read-only or not:

Try to change the value of the first element:

Traceback (most recent call last):

File "19236bd0-0bd9-11e7-a232-c706d0968eb6.py", line 6, in

x[0] = 1

ValueError: assignment destination is read-only

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**68.** Write a NumPy program (using NumPy) to sum of all the multiples of 3 or 5 below 100. Go to the editor

Expected Output:

[ 3 5 6 9 10 12 15 18 20 21 24 25 27 30 33 35 36 39 40 42 45 48 50 51 54

55 57 60 63 65 66 69 70 72 75 78 80 81 84 85 87 90 93 95 96 99]

2318

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**69.** Write a NumPy program to create an array with 10^3 elements. Go to the editor

Expected Output:

[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11.

12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23.

24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35.

- - - - - - - - - - - - - - - - -

972. 973. 974. 975. 976. 977. 978. 979. 980. 981. 982. 983.

984. 985. 986. 987. 988. 989. 990. 991. 992. 993. 994. 995.

996. 997. 998. 999.]

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**70.** Write a NumPy program to create display every element of a NumPy array. Go to the editor

Expected Output:

0 1 2 3 4 5 6 7 8 9 10 11

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**71.** Write a NumPy program to create and display every element of a NumPy array in Fortran order. Go to the editor

Expected Output:

Elements of the array in Fortan array:

0 4 8 1 5 9 2 6 10 3 7 11

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**72.** Write a NumPy program to create a 5x5x5 cube of 1's. Go to the editor

Expected Output:

[[[1 1 1 1 1]

[1 1 1 1 1]

[1 1 1 1 1]

[1 1 1 1 1]

[1 1 1 1 1]]

............

[[1 1 1 1 1]

[1 1 1 1 1]

[1 1 1 1 1]

[1 1 1 1 1]

[1 1 1 1 1]]]

Click me to see the sample solution

**73.** Write a NumPy program to create an array of (3, 4) shape, multiply every element value by 3 and display the new array. Go to the editor

Expected Output:

Original array elements:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]]

New array elements:

[[ 0 3 6 9]

[12 15 18 21]

[24 27 30 33]]

Click me to see the sample solution

**74.** Write a NumPy program to combine a one and a two dimensional array together and display their elements. Go to the editor

Expected Output:

One dimensional array:

[0 1 2 3]

Two dimensional array:

[[0 1 2 3]

[4 5 6 7]]

0:0

1:1

2:2

3:3

0:4

1:5

2:6

3:7

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**75.** Write a NumPy program to create an array of zeros and three column types (integer, float, character). Go to the editor

Expected Output:

[(1, 2., b'Albert Einstein') (2, 2., b'Edmond Halley')

(3, 3., b'Gertrude B. Elion')]

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**76.** Write a NumPy program to create a function cube which cubes all the elements of an array. Go to the editor

Expected Output:

[ 1 8 27]

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**77.** Write a NumPy program to create an array of (3, 4) shape and convert the array elements in smaller chunks. Go to the editor

Expected Output:

Original array elements:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]]

[0 4 8]

[1 5 9]

[ 2 6 10]

[ 3 7 11]

Click me to see the sample solution

**78.** Write a NumPy program to create a record array from a (flat) list of arrays. Go to the editor

Sample arrays: [1,2,3,4], ['Red', 'Green', 'White', 'Orange'], [12.20,15,20,40]

Expected Output:

(1, 'Red', 12.2)

(2, 'Green', 15.0)

(3, 'White', 20.0)

Click me to see the sample solution

**79.** Write a NumPy program to generate a generic 2D Gaussian-like array. Go to the editor

Expected Output:

2D Gaussian-like array:

[[ 0.36787944 0.44822088 0.51979489 0.57375342 0.60279818 0.60279818

0.57375342 0.51979489 0.44822088 0.36787944]

..........

[ 0.36787944 0.44822088 0.51979489 0.57375342 0.60279818 0.60279818

0.57375342 0.51979489 0.44822088 0.36787944]]

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**80.** Write a NumPy program to convert a NumPy array into Python list structure. Go to the editor

Expected Output:

Original array elements:

[[0 1]

[2 3]

[4 5]]

Array to list:

[[0, 1], [2, 3], [4, 5]]

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**81.** Write a NumPy program to access an array by column. Go to the editor

Expected Output:

Original array elements:

[[0 1]

[2 3]

[4 5]]

Access an array by column:

First column:

[0 1]

Second column:

[2 3]

Third column:

[4 5]

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**82.** Write a NumPy program to convert a NumPy array of float values to a NumPy array of integer values. Go to the editor

Expected Output:

Original array elements:

[[ 12. 12.51]

[ 2.34 7.98]

[ 25.23 36.5 ]]

Convert float values to intger values:

[[12 12]

[ 2 7]

[25 36]]

Click me to see the sample solution

**83.** Write a NumPy program to display NumPy array elements of floating values with given precision. Go to the editor

Expected Output:

Original array elements:

[ 0.26153123 0.52760141 0.5718299 0.5927067 0.7831874 0.69746349

0.35399976 0.99469633 0.0694458 0.54711478]

Print array values with precision 3:

[ 0.262 0.528 0.572 0.593 0.783 0.697 0.354 0.995 0.069 0.547]

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**84.** Write a NumPy program to suppresses the use of scientific notation for small numbers in NumPy array. Go to the editor

Expected Output:

Original array elements:

[ 1.60000000e-10 1.60000000e+00 1.20000000e+03 2.35000000e-01]

Print array values with precision 3:

[ 0. 1.6 1200. 0.235]

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**85.** Write a NumPy program to create a NumPy array of 10 integers from a generator. Go to the editor

Expected Output:

[0 1 2 3 4 5 6 7 8 9]

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**86.** Write a NumPy program to add an extra column to a NumPy array. Go to the editor

Expected Output:

[[ 10 20 30 100]

[ 40 50 60 200]]

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**87.** Write a NumPy program to find unique rows in a NumPy array. Go to the editor

Expected Output:

Original array:

[[20 20 20 0]

.......

[10 20 20 20]]

Unique rows of the above array:

[[ 0 20 20 20]

[10 20 20 20]

[20 20 20 0]]

Click me to see the sample solution

**88.** Write a NumPy program to replace all elements of NumPy array that are greater than specified array. Go to the editor

Expected Output:

Original array:

[[ 0.42436315 0.48558583 0.32924763]

[ 0.7439979 0.58220701 0.38213418]

[ 0.5097581 0.34528799 0.1563123 ]]

Replace all elements of the said array with .5 which are greater than. 5

[[ 0.42436315 0.48558583 0.32924763]

[ 0.5 0.5 0.38213418]

[ 0.5 0.34528799 0.1563123 ]]

Click me to see the sample solution

**89.** Write a NumPy program to remove specific elements in a NumPy array. Go to the editor

Expected Output:

Original array:

[ 10 20 30 40 50 60 70 80 90 100]

Delete first, fourth and fifth elements:

[ 20 30 60 70 80 90 100]

Click me to see the sample solution

**90.** Write a NumPy program to replace the negative values in a NumPy array with 0. Go to the editor

Expected Output:

Original array:

[-1 -4 0 2 3 4 5 -6]

Replace the negative values of the said array with 0:

[0 0 0 2 3 4 5 0]

Click me to see the sample solution

**91.** Write a NumPy program to remove all rows in a NumPy array that contain non-numeric values. Go to the editor

Expected Output:

Original array:

[[ 1. 2. 3.]

[ 4. 5. nan]

[ 7. 8. 9.]

[ 1. 0. 1.]]

Remove all non-numeric elements of the said array

[[ 1. 2. 3.]

[ 7. 8. 9.]

[ 1. 0. 1.]]

Click me to see the sample solution

**92.** Write a NumPy program to select indices satisfying multiple conditions in a NumPy array. Go to the editor

Sample array :

a = np.array([97, 101, 105, 111, 117])

b = np.array(['a','e','i','o','u'])

Note: Select the elements from the second array corresponding to elements in the first array that are greater than 100 and less than 110

Expected Output:

Original arrays

[ 97 101 105 111 117]

['a' 'e' 'i' 'o' 'u']

Elements from the second array corresponding to elements in the first

array that are greater than 100 and less than 110:

['e' 'i']

Click me to see the sample solution

**93.** Write a NumPy program to get the magnitude of a vector in NumPy. Go to the editor

Expected Output:

Original array:

[1 2 3 4 5]

Magnitude of the vector:

7.4161984871

Click me to see the sample solution

**94.** Write a NumPy program to count the frequency of unique values in NumPy array. Go to the editor

Expected Output:

Original array:

[10 10 20 10 20 20 20 30 30 50 40 40]

Frequency of unique values of the said array:

[[10 20 30 40 50]

[ 3 4 2 2 1]]

Click me to see the sample solution

**95.** Write a NumPy program to check whether the NumPy array is empty or not. Go to the editor

Expected Output:

2

0

Click me to see the sample solution

**96.** Write a NumPy program to divide each row by a vector element. Go to the editor

Expected Output:

Original array:

[[20 20 20]

[30 30 30]

[40 40 40]]

Vector:

[20 30 40]

[[ 1. 1. 1.]

[ 1. 1. 1.]

[ 1. 1. 1.]]

Click me to see the sample solution

**97.** Write a NumPy program to print all the values of an array. Go to the editor

Expected Output:

[[ 0. 0. 0. 0.]

[ 0. 0. 0. 0.]

[ 0. 0. 0. 0.]

[ 0. 0. 0. 0.]]

Click me to see the sample solution

**98.** Write a NumPy program to convert the raw data in an array to a binary string and then create an array. Go to the editor

Expected Output:

Original array:

[ 10. 20. 30.]

Binary string array:

b'\x00\x00\x00\x00\x00\[email protected]\x00\x00\x00\x00\x00\[email protected]\x00\x00\x00\x00\x00\x00>@'

Array using fromstring():

[ 10. 20. 30.]

Click me to see the sample solution

**99.** Write a NumPy program to sum and compute the product of a NumPy array elements. Go to the editor

Expected Output:

Original array:

[ 10. 20. 30.]

Sum of the array elements:

60.0

Product of the array elements:

6000.0

Click me to see the sample solution

**100.** Write a NumPy program to take values from a source array and put them at specified indices of another array. Go to the editor

Expected Output:

[ 10. 10. 20. 30. 30.]

Put 0 and 40 in first and fifth position of the above array

Array x after put two values:
[ 0. 10. 20. 30. 40.]

Click me to see the sample solution

**101.** Write a NumPy program to print the full NumPy array, without truncation. Go to the editor

Truncated output:

[ 0 1 2 ... 1997 1998 1999]

Click me to see the sample solution

**102.** Write a NumPy program to convert a NumPy array into a csv file. Go to the editor

Click me to see the sample solution

**103.** Write a NumPy program to calculate the Euclidean distance. Go to the editor

From Wikipedia:

In mathematics, the Euclidean distance or Euclidean metric is the "ordinary" straight-line distance between two points in Euclidean space. With this distance, Euclidean space becomes a metric space. The associated norm is called the Euclidean norm. Older literature refers to the metric as the Pythagorean metric.

Sample Output:

Euclidean distance: 5.196152422706632

Click me to see the sample solution

**104.** Write a NumPy program to access last two columns of a multidimensional columns. Go to the editor

Sample Output:

[[1 2 3]

[4 5 6]

[7 8 9]]

[[2 3]

[5 6]

[8 9]]

Click me to see the sample solution

**105.** Write a NumPy program to read a CSV data file and store records in an array. Go to the editor

Sample CSV file: fdata.csv

Date,Open,High,Low,Close

03-10-16,774.25,776.065002,769.5,772.559998

.................

07-10-16,779.659973,779.659973,770.75,775.080017

Sample Output:

[(b'Date', nan, nan, nan, nan)

(b'03-10-16', 774.25, 776.065, 769.5 , 772.56)

......................

(b'07-10-16', 779.66, 779.66 , 770.75, 775.08)]

Click me to see the sample solution

**106.** Write a NumPy program to count the occurrence of a specified item in a given NumPy array. Go to the editor

Sample Output:

Original array:

[10 20 20 20 20 0 20 30 30 30 0 0 20 20 0]

1

7

3

4

Click me to see the sample solution

**107.** Write a NumPy program to calculate percentiles for a sequence or single-dimensional NumPy array. Go to the editor

Sample Output:

50th percentile (median):

3.0

40th percentile:

2.6

90th percentile:

4.6

Click me to see the sample solution

**108.** Write a NumPy program to convert a PIL Image into a NumPy array. Go to the editor

Sample Output:

[[[255 255 255 0]

.......

[255 255 255 0]]]

Click me to see the sample solution

**109.** Write a NumPy program to convert a NumPy array to an image. Display the image. Go to the editor

Sample Output:

Click me to see the sample solution

**110.** Write a NumPy program to remove nan values from a given array. Go to the editor

Sample Output:

Original array:

[200. 300. nan nan nan 700.]

After removing nan values:

[200. 300. 700.]

Original array:

[[ 1. 2. 3.]

[nan 0. nan]

[ 6. 7. nan]]

After removing nan values:

[1. 2. 3. 0. 6. 7.]

Click me to see the sample solution

**111.** Write a NumPy program to create a Cartesian product of two arrays into single array of 2D points. Go to the editor

Sample Output:

[[1 4]

......

[3 5]]

Click me to see the sample solution

**112.** Write a NumPy program to get the memory usage by NumPy arrays. Go to the editor

Sample Output:

8256

Click me to see the sample solution

**113.** Write a NumPy program to build an array of all combinations of three NumPy arrays. Go to the editor

Sample Output:

Original arrays:

Array-1

[1, 2, 3]

Array-2

[4, 5]

Array-3

[6, 7]

Combine array:

[[1 4 6]

........

[3 4 7]

[3 5 7]]

Click me to see the sample solution

**114.** Write a NumPy program to create random set of rows from 2D array. Go to the editor

Sample Output:

Random set of rows from 2D array array:

[[4 0 2]

.......

[3 4 3]]

Click me to see the sample solution

**115.** Write a NumPy program to find indices of elements equal to zero in a NumPy array. Go to the editor

Sample Output:

Original array:

[1 0 2 0 3 0 4 5 6 7 8]

Indices of elements equal to zero of the said array:

[1 3 5]

Click me to see the sample solution

**116.** Write a NumPy program to compute the histogram of a set of data. Go to the editor

Sample Output:

Click me to see the sample solution

**117.** Write a NumPy program to compute the line graph of a set of data. Go to the editor

Sample Output:

Click me to see the sample solution

**118.** Write a NumPy program to find the position of the index of a specified value greater than existing value in NumPy array. Go to the editor

Sample Output:

Original array:

[-6 -5 -4 -3 -2 -1 0 1 2 3 4 5]

Position of the index:

9

Click me to see the sample solution

**119.** Write a NumPy program to add a new row to an empty NumPy array. Go to the editor

Sample Output:

Empty array:

[]

After adding two new arrays:

[[10 20 30]

[40 50 60]]

Click me to see the sample solution

**120.** Write a NumPy program to get the index of a maximum element in a NumPy array along one axis. Go to the editor

Sample Output:

Original array:

[[1 2 3]

[4 3 1]]

Index of a maximum element in a NumPy array along one axis:

4

Click me to see the sample solution

**121.** Write a NumPy program to join a sequence of arrays along a new axis. Go to the editor

Sample Output:

Original arrays:

[1 2 3]

[2 3 4]

Sequence of arrays along a new axis:

[[1 2 3]

[2 3 4]]

Original arrays:

[[1]

[2]

[3]]

[[2]

[3]

[4]]

Sequence of arrays along a new axis:

[[1]

[2]

[3]

[2]

[3]

[4]]

Click me to see the sample solution

**122.** Write a NumPy program to find the index of the sliced elements as follows from a given 4x4 array. Go to the editor

Sample Output:

Original arrays:

[[ 0 1 2 3]

........

[12 13 14 15]]

Sliced elements:

[ 0 5 11]

Click me to see the sample solution

**123.** Write a NumPy program to create two arrays of size bigger and smaller than a given array. Go to the editor

Sample Output:

Original arrays:

[[ 0 1 2 3]

........

[12 13 14 15]]

Array with size 2x2 from the said array:

[[0 1]

[2 3]]

Array with size 6x6 from the said array:

[[ 0 1 2 3 4 5]

.........

[14 15 0 1 2 3]]

Click me to see the sample solution

**124.** Write a NumPy program to broadcast on different shapes of arrays where p(3,3) + q(3). Go to the editor

Sample Output:

Original arrays:

Array-1

[[0 0 0]

[1 2 3]

[4 5 6]]

Array-2

[10 11 12]

New Array:

[[10 11 12]

[11 13 15]

[14 16 18]]

Click me to see the sample solution

**125.** Write a NumPy program to broadcast on different shapes of arrays where a(,3) + b(3). Go to the editor

Sample Output:

Original arrays:

Array-1

[[ 0]

[10]

[20]]

Array-2

[10 11 12]

New Array:

[[10 11 12]

[20 21 22]

[30 31 32]]

Click me to see the sample solution

**126.** Write a NumPy program to rearrange the dimensions of a given array. Go to the editor

Sample Output:

Original arrays:

[[ 0 1 2 3]

...........

[20 21 22 23]]

After reverse the dimensions:

[[ 0 4 8 12 16 20]

............

[ 3 7 11 15 19 23]]

Click me to see the sample solution

**127.** Write a NumPy program to stack arrays in sequence horizontally (column wise). Go to the editor

Sample Output:

Original arrays:

Array-1

[[0 1 2]

[3 4 5]

[6 7 8]]

Array-2

[[ 0 3 6]

[ 9 12 15]

[18 21 24]]

Stack arrays in sequence horizontally:

[[ 0 1 2 0 3 6]

[ 3 4 5 9 12 15]

[ 6 7 8 18 21 24]]

Click me to see the sample solution

**128.** Write a NumPy program to stack arrays in sequence vertically. Go to the editor

Sample Output:

Original arrays:

Array-1

[[0 1 2]

[3 4 5]

[6 7 8]]

Array-2

[[ 0 3 6]

[ 9 12 15]

[18 21 24]]

Stack arrays in sequence vertically:

[[ 0 1 2]

...........

[18 21 24]]

Click me to see the sample solution

**129.** Write a NumPy program to stack 1-D arrays as columns wise. Go to the editor

Sample Output:

Original arrays:

Array-1

[1 2 3]

Array-2

[2 3 4]

Stack 1-D arrays as columns wise:

[[1 2]

[2 3]

[3 4]]

Click me to see the sample solution

**130.** Write a NumPy program to stack 1-D arrays as row wise. Go to the editor

Sample Output:

Original arrays:

Array-1

[1 2 3]

Array-2

[2 3 4]

Stack 1-D arrays as rows wise:

[[1 2 3]

[2 3 4]]

Click me to see the sample solution

**131.** Write a NumPy program to split a given array into multiple sub-arrays vertically (row-wise). Go to the editor

Sample Output:

Original arrays:

[[ 0. 1. 2. 3.]

.............

[12. 13. 14. 15.]]

Split an array into multiple sub-arrays vertically:

[array([[0., 1., 2., 3.],

[4., 5., 6., 7.]]), array([[ 8., 9., 10., 11.],

[12., 13., 14., 15.]])]

Click me to see the sample solution

**132.** Write a NumPy program to split array into multiple sub-arrays along the 3rd axis. Go to the editor

Sample Output:

Original arrays:

[[[ 0. 1. 2. 3.]

[ 4. 5. 6. 7.]]

[[ 8. 9. 10. 11.]

[12. 13. 14. 15.]]]

split array into multiple sub-arrays along the 3rd axis:

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

[ 4., 5.]],

[[ 8., 9.],

[12., 13.]]]), array([[[ 2., 3.],

[ 6., 7.]],

[[10., 11.],

[14., 15.]]])]

Click me to see the sample solution

**133.** Write a NumPy program to count the number of dimensions, number of elements and number of bytes for each element in a given array. Go to the editor

Sample Output:

Original arrays:

[[ 0 1 2 3 4 5 6 7 8 9 10 11]

[12 13 14 15 16 17 18 19 20 21 22 23]]

Number of dimensions:

2

Number of elements:

24

Number of bytes for each element in the said array:

8

Click me to see the sample solution

**134.** Write a NumPy program to extract all the elements of the first row from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: First row

[0 1 2 3]

Click me to see the sample solution

**135.** Write a NumPy program to extract all the elements of the second row from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: Second row

[4 5 6 7]

Click me to see the sample solution

**136.** Write a NumPy program to extract all the elements of the third column from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: Third column

[ 2 6 10 14]

Click me to see the sample solution

**137.** Write a NumPy program to extract first and second elements of the first and second rows from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: First and second elements of the first and second rows

[[0 1]

[4 5]]

Click me to see the sample solution

**138.** Write a NumPy program to extract third and fourth elements of the first and second rows from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: Third and fourth elements of the first and second rows

[[2 3]

[6 7]]

Click me to see the sample solution

**139.** Write a NumPy program to extract first and third elements of the first and third rows from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: First and third elements of the first and third rows

[[ 0 2]

[ 8 10]]

Click me to see the sample solution

**140.** Write a NumPy program to extract second and fourth elements of the second and fourth rows from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: Second and fourth elements of the second and fourth rows

[[ 5 7]

[13 15]]

Click me to see the sample solution

**141.** Write a NumPy program to extract all the elements of the second and third columns from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: All the elements of the second and third columns

[[ 1 2]

[ 5 6]

[ 9 10]

[13 14]]

Click me to see the sample solution

**142.** Write a NumPy program to extract all the elements of the first and fourth columns from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: All the elements of the first and fourth columns

[[ 0 3]

[ 4 7]

[ 8 11]

[12 15]]

Click me to see the sample solution

**143.** Write a NumPy program to extract first element of the second row and fourth element of fourth row from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: First element of the second row and fourth element of fourth row

[ 4 15]

Click me to see the sample solution

**144.** Write a NumPy program to extract second and third elements of the second and third rows from a given (4x4) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]

[12 13 14 15]]

Extracted data: Second and third elements of the second and third rows

[[ 5 6]

[ 9 10]]

Click me to see the sample solution

**145.** Write a NumPy program to extract first, third and fifth elements of the third and fifth rows from a given (6x6) array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3 4 5]

................

[30 31 32 33 34 35]]

Extracted data: First, third and fifth elements of the third and fifth rows

[[12 14 16]

[24 26 28]]

Click me to see the sample solution

**146.** Write a NumPy program to add two arrays A and B of sizes (3,3) and (,3). Go to the editor

Sample Output:

Original array:

Array-1

[[1. 1. 1.]

[1. 1. 1.]

[1. 1. 1.]]

Array-2

[0 1 2]

A + B:

[[1. 2. 3.]

[1. 2. 3.]

[1. 2. 3.]]

Click me to see the sample solution

**147.** Write a NumPy program to create an array that represents the rank of each item of a given array. Go to the editor

Sample Output:

Original array:

[24 27 30 29 18 14]

Rank of each item of the said array:

[2 3 5 4 1 0]

Click me to see the sample solution

**148.** Write a NumPy program to copy data from a given array to another array. Go to the editor

Sample Output:

Original array:

[24 27 30 29 18 14]

Copy of the said array:

[24 27 30 29 18 14]

Click me to see the sample solution

**149.** Write a NumPy program to find elements within range from a given array of numbers. Go to the editor

Sample Output:

Original array:

[ 1 3 7 9 10 13 14 17 29]

Elements within range: index position

(array([2, 3, 4, 5, 6, 7]),)

Click me to see the sample solution

**150.** Write a NumPy program to swap columns in a given array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3]

[ 4 5 6 7]

[ 8 9 10 11]]

After swapping arrays:

[[ 1 0 2 3]

[ 5 4 6 7]

[ 9 8 10 11]]

Click me to see the sample solution

**151.** Write a NumPy program to get the row numbers in given array where at least one item is larger than a specified value. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3 4 5 6 7 8]

[ 9 10 11 12 13 14 15 16 17]

[18 19 20 21 22 23 24 25 26]

[27 28 29 30 31 32 33 34 35]]

Row numbers where at least one item is larger than 10:

(array([1, 2, 3]),)

Click me to see the sample solution

**152.** Write a NumPy program to calculate the sum of all columns of a 2D NumPy array. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3 4 5 6 7 8]

[ 9 10 11 12 13 14 15 16 17]

[18 19 20 21 22 23 24 25 26]

[27 28 29 30 31 32 33 34 35]]

Sum of all columns:

[54 58 62 66 70 74 78 82 86]

Click me to see the sample solution

**153.** Write a NumPy program to extract upper triangular part of a NumPy matrix. Go to the editor

Sample Output:

Original array:

[[ 0 1 2]

...........

[15 16 17]]

Extract upper triangular part of the said array:

[0 1 2 4 5 8]

Extract upper triangular part of the said array:

[0 1 4]

Click me to see the sample solution

**154.** Write a NumPy program to get a copy of a matrix with the elements below the k-th diagonal zeroed. Go to the editor

Sample Output:

Original array:

[[1 2 3]

[0 5 6]

[0 0 9]

[0 0 0]]

Copy of a matrix with the elements below the k-th diagonal zeroed:

[[1 2 3]

[0 5 6]

[0 0 9]

[0 0 0]]

Click me to see the sample solution

**155.** Write a NumPy program to check whether a Numpy array contains a specified row. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3 4]

[ 5 6 7 8 9]

[10 11 12 13 14]

[15 16 17 18 19]]

True

False

True

Click me to see the sample solution

**156.** Write a NumPy program to calculate averages without NaNs along a given array. Go to the editor

Sample Output:

Original array:

[[10. 20. 30.]

[40. 50. nan]

[nan 6. nan]

[nan nan nan]]

Averages without NaNs along the said array:

[20. 45. 6. nan]

Click me to see the sample solution

**157.** Write a NumPy program to create a new array which is the average of every consecutive triplet of elements of a given array. Go to the editor

Sample Output:

Original array:

[ 1 2 3 2 4 6 1 2 12 0 -12 6]

Average of every consecutive triplet of elements of the said array:

[ 2. 4. 5. -2.]

Click me to see the sample solution

**158.** Write a NumPy program to calculate average values of two given NumPy arrays. Go to the editor

Sample Output:

Original arrays:

[[0, 1], [2, 3]]

[[4, 5], [0, 3]]

Average values of two said NumPy arrays:

[[2. 3.]

[1. 3.]]

Click me to see the sample solution

**159.** Write a NumPy program to rearrange columns of a given NumPy 2D array using given index positions. Go to the editor

Sample Output:

Original arrays:

[[ 11 22 33 44 55]

[ 66 77 88 99 100]]

New array:

[[ 22 44 11 55 33]

[ 77 99 66 100 88]]

Click me to see the sample solution

**160.** Write a NumPy program to find the k smallest values of a given NumPy array. Go to the editor

Sample Output:

Original arrays:

[ 1. 7. 8. 2. 0.1 3. 15. 2.5]

k smallest values:

[0.1 1. 2. 2.5]

Click me to see the sample solution

**161.** Write a NumPy program to create a white image of size 512x256. Go to the editor

Sample Output:

Click me to see the sample solution

**162.** Create an array (a) of shape 3, 4, 8 (K=3, J=4, I=8). tidx is an array of the same length as a.shape[1], i.e. contains J = 4 elements where each index denotes which element of K should be chosen.

Write a NumPy program to select from the first axis (K) by the indices tidx to get an array of shape (J=4, I=8) back. Go to the editor

Sample Output:

Original array and shape:

[[[3 2 2 7 7 7 0 3]

[5 8 4 2 9 9 3 9]

[6 8 2 8 5 7 8 7]

[5 2 4 0 4 9 2 5]]

------------------

tidex: [0 2 2 2]

Result:

[[3 2 2 7 7 7 0 3]

[3 9 2 6 3 3 1 0]

[5 4 0 6 0 2 7 8]

[6 3 1 8 8 1 5 7]]

Click me to see the sample solution

**163.** Create two arrays of six elements. Write a NumPy program to count the number of instances of a value occurring in one array on the condition of another array. Go to the editor

Sample Output:

Original arrays:

[ 10 -10 10 -10 -10 10]

[0.85 0.45 0.9 0.8 0.12 0.6 ]

Number of instances of a value occurring in one array on the condition of another array:

3

Click me to see the sample solution

**164.** Write a NumPy program to save as text a matrix which has in each row 2 float and 1 string at the end. Go to the editor

Sample Output:

string

1 0 aaa

0 1 bbb

0 1 ccc

Click me to see the sample solution

**165.** Write a NumPy program to merge three given NumPy arrays of same shape. Go to the editor

Click me to see the sample solution

**166.** Write a NumPy program to combine last element with first element of two given ndarray with different shapes. Go to the editor

Sample Output:

Original arrays:

['PHP', 'JS', 'C++']

['Python', 'C#', 'NumPy']

After Combining:

['PHP' 'JS' 'C++Python' 'C#' 'NumPy']

Click me to see the sample solution

**167.** Write a NumPy program to convert a Python dictionary to a NumPy ndarray. Go to the editor

Sample Output:

Original dictionary:

{'column0': {'a': 1, 'b': 0.0, 'c': 0.0, 'd': 2.0},

'column1': {'a': 3.0, 'b': 1, 'c': 0.0, 'd': -1.0},

'column2': {'a': 4, 'b': 1, 'c': 5.0, 'd': -1.0},

'column3': {'a': 3.0, 'b': -1.0, 'c': -1.0, 'd': -1.0}}

Type: <class 'dict'>

ndarray:

[[ 1. 0. 0. 2.]

[ 3. 1. 0. -1.]

[ 4. 1. 5. -1.]

[ 3. -1. -1. -1.]]

Type: <class 'numpy.ndarray'>

Click me to see the sample solution

**168.** Write a NumPy program to convert Pandas dataframe to NumPy array with headers. Go to the editor

Sample Output:

Original NumPy array:

[[0.18308157 0.32258608 0.39644848]

[0.31018507 0.08220454 0.40018982]

[0.63639779 0.34908174 0.39878868]

............

[0.02482073 0.02318678 0.36032194]

[0.69001834 0.04285817 0.31768865]]

Type: <class 'numpy.ndarray'>

Panda's DataFrame:

A B C

0 0.015583 0.968431 0.943192

1 0.221607 0.704098 0.241200

2 0.466129 0.269226 0.450781

3 0.747222 0.674508 0.686070

............

10 0.272827 0.817238 0.093650

11 0.196416 0.643602 0.262683

Type: <class 'pandas.core.frame.DataFrame'>

Click me to see the sample solution

**169.** Write a NumPy program to get all 2D diagonals of a 3D NumPy array. Go to the editor

Sample Output:

Original NumPy array:

[[[ 0 1 2 3 4]

[ 5 6 7 8 9]

[10 11 12 13 14]

[15 16 17 18 19]]

............

[[40 41 42 43 44]

[45 46 47 48 49]

[50 51 52 53 54]

[55 56 57 58 59]]]

Type: <class 'numpy.ndarray'>

2D diagonals:

[[ 0 6 12 18]

[20 26 32 38]

[40 46 52 58]]

Type: <class 'numpy.ndarray'>

Click me to see the sample solution

**170.** Create a 2-dimensional array of size 2 x 3, composed of 4-byte integer elements. Write a NumPy program to find the number of occurrences of a sequence in the said array. Go to the editor

Sample Output:

Original NumPy array:

[[1 2 3]

[2 1 2]]

Type: <class 'numpy.ndarray'>

Sequence: 2,3

Number of occurrences of the said sequence: 2

Click me to see the sample solution

**171.** Write a NumPy program to search the index of a given array in another given array. Go to the editor

Sample Output:

Original NumPy array:

[[ 1 2 3]

[ 4 5 6]

[ 7 8 9]

[10 11 12]]

Searched array:

[4 5 6]

Index of the searched array in the original array:

[1]

Click me to see the sample solution

**172.** Write a NumPy program to find and store non-zero unique rows in an array after comparing each row with other row in a given matrix. Go to the editor

Sample Output:

Original array:

[[ 1 1 0]

[ 0 0 0]

[ 0 2 3]

[ 0 0 0]

[ 0 -1 1]

[ 0 0 0]]

Non-zero unique rows:

[[ 1 1 0]

[ 0 2 3]

[ 0 -1 1]]

Click me to see the sample solution

**173.** Write a NumPy program to set zero to lower triangles along the last two axes of a three-dimensional of a given array. Go to the editor

Sample Output:

Original array:

[[[1. 1. 1. 1. 1. 1. 1. 1.]

[1. 1. 1. 1. 1. 1. 1. 1.]

..............

[1. 1. 1. 1. 1. 1. 1. 1.]]]

Result:

[[[0. 1. 1. 1. 1. 1. 1. 1.]

[0. 0. 1. 1. 1. 1. 1. 1.]

.................

[0. 0. 0. 0. 0. 0. 0. 0.]]]

Click me to see the sample solution

**174.** Write a NumPy program to get the number of items, array dimensions, number of array dimensions and the memory size of each element of a given array. Go to the editor

Sample Output:

Original array:

[[ 1 2 3 4]

[ 5 6 7 8]

[ 9 10 11 12]]

Number of items of the said array:

12

Array dimensions:

(3, 4)

Number of array dimensions:

2

Memory size of each element of the said array

8

Click me to see the sample solution

**175.** Write a NumPy program to create an 1-D array of 20 elements. Now create a new array of shape (5, 4) from the said array, then restores the reshaped array into a 1-D array. Go to the editor

Sample Output:

Original array:

[ 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38]

New array of shape(5, 3):

[[ 0 2 4 6]

[ 8 10 12 14]

[16 18 20 22]

[24 26 28 30]

[32 34 36 38]]

Restore the reshaped array into a 1-D array:

[ 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38]

Click me to see the sample solution

**176.** Write a NumPy program to create an array of 4,5 shape and swap column1 with column4. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3 4]

[ 5 6 7 8 9]

[10 11 12 13 14]

[15 16 17 18 19]]

After swapping column1 with column4:

[[ 3 1 2 0 4]

[ 8 6 7 5 9]

[13 11 12 10 14]

[18 16 17 15 19]]

Click me to see the sample solution

**177.** Write a NumPy program to create an array of 4,5 shape and to reverse the rows of the said array. After reversing 1st row will be 4th and 4th will be 1st, 2nd row will be 3rd row and 3rd row will be 2nd row. Go to the editor

Sample Output:

Original array:

[[ 0 1 2 3 4]

[ 5 6 7 8 9]

[10 11 12 13 14]

[15 16 17 18 19]]

After reversing:

[[15 16 17 18 19]

[10 11 12 13 14]

[ 5 6 7 8 9]

[ 0 1 2 3 4]]

Click me to see the sample solution

**178.** Write a NumPy program to replace all the nan (missing values) of a given array with the mean of another array. Go to the editor

Sample Output:

Original arrays:

[[ 0 1 2 3 4]

[ 5 6 7 8 9]

[10 11 12 13 14]

[15 16 17 18 19]]

[[ 1. 2. nan]

[ 4. 5. 6.]

[nan 7. nan]]

All the nan of array_nums2 replaced by the mean of array_nums1:

[[1. 2. 9.5]

[4. 5. 6. ]

[9.5 7. 9.5]]

Click me to see the sample solution

**179.** Write a NumPy program to fetch all items from a given array of 4,5 shape which are either greater than 6 and a multiple of 3. Go to the editor

Sample Output:

Original arrays:

[[ 0 1 2 3 4]

[ 5 6 7 8 9]

[10 11 12 13 14]

[15 16 17 18 19]]

Items greater than 6 and a multiple of 3 of the said array:

[ 9 12 15 18]

Click me to see the sample solution

**180.** Write a NumPy program to check whether the dimensions of two given arrays are same or not. Go to the editor

Click me to see the sample solution

**181.** Write a NumPy program to place a specified element in specified time randomly in a specified 2D array. Go to the editor

Sample Output:

Original array:

[[0. 0. 0. 0.]

[0. 0. 0. 0.]

[0. 0. 0. 0.]

[0. 0. 0. 0.]]

Place a specified element in specified time randomly:

[[10. 0. 0. 0.]

[10. 0. 0. 0.]

[ 0. 0. 0. 10.]

[ 0. 0. 0. 0.]]

Click me to see the sample solution

**182.** Write a NumPy program to subtract the mean of each row of a given matrix. Go to the editor

Sample Output:

Original matrix:

[[0.59243452 0.51883289 0.03732848 0.49544926 0.22637201 0.45750412

0.81614237 0.86681236 0.95482226 0.54789281]

..............

[0.14428353 0.20556412 0.97059136 0.53545871 0.93828877 0.81535277

0.60563373 0.47543413 0.0468766 0.97460889]]

Subtract the mean of each row of the said matrix:

[[ 0.04107541 -0.03252622 -0.51403063 -0.05590985 -0.3249871 -0.09385499

0.26478326 0.31545325 0.40346315 -0.0034663 ]

....................

[-0.42692573 -0.36564514 0.3993821 -0.03575056 0.36707951 0.24414351

0.03442447 -0.09577513 -0.52433266 0.40339963]]

Click me to see the sample solution

**183.** Write a NumPy program to test whether a given 2D array has null columns or not. Go to the editor

Sample Output:

Original array:

[[1 2 1 1 1 2 1 1 2 0]

[1 1 0 0 0 0 2 1 2 0]

[0 0 2 1 0 2 2 2 2 2]

[1 1 1 2 0 0 0 0 1 2]]

Test whether the said array has null columns or not:

False

Click me to see the sample solution

**184.** Write a NumPy program to create an array using generator function that generates 15 integers. Go to the editor

Sample Output:

New array:

[ 0. 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14.]

Click me to see the sample solution

**185.** Write a NumPy program to create a new vector with 2 consecutive 0 between two values of a given vector. Go to the editor

Sample Output:

Original array:

[1 2 3 4 5 6 7 8]

New array:

[1. 0. 0. 2. 0. 0. 3. 0. 0. 4. 0. 0. 5. 0. 0. 6. 0. 0. 7. 0. 0. 8.]

Click me to see the sample solution

**186.** Write a NumPy program to multiply an array of dimension (2,2,3) by an array with dimensions (2,2). Go to the editor

Sample Output:

Original array:

[[[1. 1. 1.]

[1. 1. 1.]]

[[1. 1. 1.]

[1. 1. 1.]]]

New array:

[[[3. 3. 3.]

[3. 3. 3.]]

[[3. 3. 3.]

[3. 3. 3.]]]

Click me to see the sample solution

**187.** Write a NumPy program to convert a given vector of integers to a matrix of binary representation. Go to the editor

Sample Output:

Original vector:

[ 0 1 3 5 7 9 11 13 15]

Binary representation of the said vector:

[[0 0 0 0 0 0 0 0]

[0 0 0 0 0 0 0 1]

..............

[0 0 0 0 1 1 1 1]]

Click me to see the sample solution

**188.** Write a NumPy program to extract rows with unequal values (e.g. [1,1,2]) from 10x3 matrix. Go to the editor

Sample Output:

Original vector:

[[3 2 0]

........

[3 0 2]]

Rows with unequal values:

[[3 2 0]

[2 3 1]

.........

[3 0 2]]

Click me to see the sample solution

**189.** Write a NumPy program to find rows of a given array of shape (8,3) that contain elements of each row of another given array of shape (2,2). Go to the editor

Sample Output:

Original arrays:

[[5 2 5 1]

[5 4 1 3]

..........

[4 0 4 0]]

[[2 3 1]

[1 1 4]]

Rows of a given array that contain elements of each row of another given array:

[0 1 2 4]

Click me to see the sample solution

**190.** Write a NumPy program to create a record array from a given regular array. Go to the editor

Sample Output:

Original arrays:

[['Yasemin Rayner' '88.5' '90']

['Ayaana Mcnamara' '87' '99']

['Jody Preece' '85.5' '91']]

Record array;

[(b'Yasemin Rayner', 88.5, 90) (b'Ayaana Mcnamara', 87. , 99)

(b'Jody Preece', 85.5, 91)]

Click me to see the sample solution

**191.** Write a NumPy program to get the block-sum (block size is 5x5) from a given array of shape 25x25. Go to the editor

Sample Output:

Original arrays:

[[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]

[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]

.........................

[1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1. 1.]]

Block-sum (5x5) of the said array:

[[25. 25. 25. 25. 25.]

[25. 25. 25. 25. 25.]

[25. 25. 25. 25. 25.]

[25. 25. 25. 25. 25.]

[25. 25. 25. 25. 25.]]

Click me to see the sample solution

**192.** Write a NumPy program to extract all the contiguous 4x4 blocks from a given random 12x12 matrix. Go to the editor

Sample Output:

Original arrays:

[[3 3 1 2 0 3 0 3 2 0 1 0]

[4 0 4 2 0 0 0 0 2 2 2 3]

..................

[1 2 3 4 1 2 3 4 3 2 3 4]

[4 0 4 2 2 4 1 4 2 0 0 0]]

Contiguous 4x4 blocks:

[[[[3 3 1 2]

[4 0 4 2]

[1 4 0 1]

[1 4 2 4]]

...

[[4 1 1 0]

[1 0 2 2]

[3 2 3 4]

[2 0 0 0]]]]

Click me to see the sample solution

**193.** Write a Numpy program to test whether numpy array is faster than Python list or not. Go to the editor

Time to aggregates elements from each of the iterables:

Sample Output:

List:

72.64399528503418

NumPy array:

19.61684226989746

Click me to see the sample solution

**194.** Write a NumPy program to create two arrays with shape (300,400, 5), fill values using unsigned integer (0 to 255). Insert a new axis that will appear at the beginning in the expanded array shape. Now combine the said two arrays into one. Go to the editor

Sample Output:

Array1:

[[[ 46 117 73]

[215 90 86]

[ 80 89 220]

...

[ 47 94 234]

[ 95 72 61]

[154 91 175]]

[[232 194 26]

[219 116 116]

[126 179 177]

...

Array2:

[[[ 37 10 228]

[241 52 82]

[196 47 189]

...

[127 70 246]

[158 46 12]

[ 56 129 162]]

[[224 215 47]

[139 72 13]

[218 64 78]

...

Combined array:

[[[[ 46 117 73]

[215 90 86]

[ 80 89 220]

...

[208 187 55]

[109 115 254]

[115 134 68]]

[[158 106 165]

[189 48 54]

[ 5 84 26]

...

[131 235 25]

[101 146 90]

[216 15 92]]]]

Click me to see the sample solution

**195.** Write a NumPy program to remove the first dimension from a given array of shape (1,3,4). Go to the editor

Sample Output:

Shape of the said array:

(1, 3, 4)

After removing the first dimension of the shape of the said array:

Click me to see the sample solution

**196.** Write a NumPy program to create a 12x12x4 array with random values and extract any array of shape(6,6,3) from the said array. Go to the editor

Sample Output:

Original array:

[[[0.67420382 0.5592584 0.27096382]

[0.2896283 0.68346522 0.13996167]

[0.74283318 0.06323309 0.0980022 ]

[0.43203954 0.38888969 0.44801756]

[0.04391897 0.4851516 0.34044817]

[0.2202623 0.81434798 0.51900666]

[0.12442371 0.91247823 0.01874549]

[0.2287782 0.88089638 0.40583551]]

........

[[0.28021231 0.47537742 0.72971633]

[0.87380873 0.83031311 0.56713737]

[0.23093306 0.22830678 0.54439754]

[0.88130002 0.37081258 0.78148687]

[0.00318428 0.62297164 0.58875116]

[0.68102061 0.31822913 0.04432477]

[0.70410386 0.56770957 0.42998752]

[0.5891714 0.25692428 0.19184309]]]

Extract array of shape (6,6,3) from the said array:

[[[0.67420382 0.5592584 0.27096382]

[0.2896283 0.68346522 0.13996167]

[0.74283318 0.06323309 0.0980022 ]

[0.43203954 0.38888969 0.44801756]

[0.04391897 0.4851516 0.34044817]

[0.2202623 0.81434798 0.51900666]]

.......

[[0.85965509 0.11357479 0.27325381]

[0.74156642 0.35108524 0.40305073]

[0.44791592 0.28270286 0.45377936]

[0.01543443 0.14978493 0.47738367]

[0.63671823 0.75239388 0.59118693]

[0.55932007 0.32759274 0.25519358]]]

Click me to see the sample solution

**197.** Write a NumPy program to create to concatenate two given arrays of shape (2, 2) and (2,1). Go to the editor

Sample Output:

Original arrays:

[[4.5 3.5]

[5.1 2.3]]

[[1]

[2]]

Concatenating the said two arrays:

[[4.5 3.5 1. ]

[5.1 2.3 2. ]]

Click me to see the sample solution

**198.** Write a NumPy program to create a 10x4 array filled with random floating point number values with and set the array values with specified precision. Go to the editor

Sample Output:

Original arrays:

[[-1.23335604 0.54368124 1.93500931 -0.45001639]

[ 1.20528013 2.04423279 -0.68858903 -0.46642789]

[ 1.29030601 0.60914425 0.03139104 -1.72528221]

[-0.32607231 -2.36951679 -0.80374203 -0.26212641]

[-0.16426628 -0.21524949 -0.35957311 -2.27709735]

[-0.28851276 -0.59101441 0.22293919 -0.50128832]

[ 1.3577567 0.05529019 0.81208832 0.70810424]

[ 0.46853801 -0.81857981 0.80443323 0.52391606]

[-0.29149088 -0.91153449 -1.00515549 0.31065165]

[ 2.68952752 1.86676839 1.49239198 -1.0409156 ]]

Set the array values with specified precision:

[[-1.2334 0.5437 1.935 -0.45 ]

[ 1.2053 2.0442 -0.6886 -0.4664]

[ 1.2903 0.6091 0.0314 -1.7253]

[-0.3261 -2.3695 -0.8037 -0.2621]

[-0.1643 -0.2152 -0.3596 -2.2771]

[-0.2885 -0.591 0.2229 -0.5013]

[ 1.3578 0.0553 0.8121 0.7081]

[ 0.4685 -0.8186 0.8044 0.5239]

[-0.2915 -0.9115 -1.0052 0.3107]

[ 2.6895 1.8668 1.4924 -1.0409]]

Click me to see the sample solution

**199.** Write a NumPy program to create an array using scientific notation numbers. Set the precision value to 6 and print the array. Go to the editor

Sample Output:

Original arrays:

[1.2e-07 1.5e-06 1.7e-05]

Set the precision value to 10:

[0.00000012 0.0000015 0.000017 ]

Click me to see the sample solution

**200.** Write a NumPy program to remove a specific column from a given array. Go to the editor

Sample Output:

Original array:

[[0.54420704 0.35710194 0.79167579 0.72249474 0.99968936]

[0.22306352 0.31085825 0.09849254 0.11708716 0.45757945]

[0.19381592 0.13587749 0.90455038 0.95146017 0.55716851]

[0.62031347 0.84275698 0.84665943 0.06562172 0.58415968]

[0.41903059 0.0660559 0.85270403 0.94184265 0.95371587]

[0.02577681 0.91577282 0.1969686 0.3472482 0.23337827]

[0.43563908 0.62308811 0.09606371 0.79053989 0.69382428]]

Delete the first column of the said array:

[[0.35710194 0.79167579 0.72249474 0.99968936]

[0.31085825 0.09849254 0.11708716 0.45757945]

[0.13587749 0.90455038 0.95146017 0.55716851]

[0.84275698 0.84665943 0.06562172 0.58415968]

[0.0660559 0.85270403 0.94184265 0.95371587]

[0.91577282 0.1969686 0.3472482 0.23337827]

[0.62308811 0.09606371 0.79053989 0.69382428]]

Delete the last column of the said array:

[[0.54420704 0.35710194 0.79167579 0.72249474]

[0.22306352 0.31085825 0.09849254 0.11708716]

[0.19381592 0.13587749 0.90455038 0.95146017]

[0.62031347 0.84275698 0.84665943 0.06562172]

[0.41903059 0.0660559 0.85270403 0.94184265]

[0.02577681 0.91577282 0.1969686 0.3472482 ]

[0.43563908 0.62308811 0.09606371 0.79053989]]

Click me to see the sample solution

**201.** Write a NumPy program to create a 90x30 array filled with random point numbers, increase the number of items (10 edge elements) shown by the print statement. Go to the editor

Sample Output:

Original array:

[[1 8 3 ... 9 5 8]

[1 9 6 ... 6 5 0]

[0 0 8 ... 6 9 8]

...

[2 3 9 ... 4 0 1]

[2 6 8 ... 8 3 4]

[1 2 9 ... 7 4 8]]

Increase the number of items (10 edge elements) shown by the print statement:

[[1 8 3 0 1 2 8 0 0 5 ... 1 3 8 1 1 7 5 9 5 8]

[1 9 6 1 0 7 7 3 8 6 ... 5 9 9 9 9 7 2 6 5 0]

[0 0 8 1 4 2 1 3 2 9 ... 5 6 4 1 4 9 0 6 9 8]

[7 2 7 1 7 2 4 7 2 0 ... 4 2 6 2 6 4 4 0 6 7]

[3 6 0 0 2 1 6 6 2 9 ... 3 4 1 9 5 7 4 4 6 7]

[9 5 2 6 9 2 7 7 9 6 ... 4 3 5 2 7 0 6 0 2 7]

[5 5 4 1 9 2 5 3 5 2 ... 7 4 7 5 5 7 3 0 1 8]

[5 9 9 9 6 3 5 0 9 4 ... 6 4 9 7 8 7 2 5 9 4]

[6 1 0 8 9 8 0 6 6 3 ... 5 3 1 6 1 5 2 9 8 3]

[3 0 3 1 4 1 4 1 9 6 ... 3 9 4 4 5 0 2 0 8 0]

...

[3 9 5 0 3 8 5 3 1 1 ... 1 2 4 6 2 4 5 0 0 5]

[7 9 7 0 1 3 0 1 8 4 ... 5 7 5 4 7 2 0 2 3 0]

[4 2 6 4 7 2 3 9 7 9 ... 2 7 1 2 5 7 5 4 0 2]

[7 8 9 7 3 3 1 2 8 5 ... 1 9 9 5 5 2 3 5 0 1]

[3 7 6 8 3 2 5 0 5 4 ... 0 4 9 8 5 3 2 1 3 3]

[3 3 8 4 0 4 8 4 7 0 ... 7 5 0 9 7 8 2 0 7 9]

[8 4 4 7 3 8 2 0 8 9 ... 5 5 8 1 5 6 0 6 5 0]

[2 3 9 9 9 8 6 5 4 4 ... 4 0 7 1 8 6 7 4 0 1]

[2 6 8 7 3 3 8 4 1 6 ... 1 3 9 5 0 1 4 8 3 4]

[1 2 9 5 1 2 9 9 5 4 ... 3 1 2 6 1 4 4 7 4 8]]

Click me to see the sample solution

**202.** Write a NumPy program to calculate the arithmetic means of corresponding elements of two given arrays of same size. Go to the editor

Sample Output:

Array1:

[[2 5 2]

[1 5 5]]

Array2:

[[5 3 4]

[3 2 5]]

Arithmetic means of corresponding elements of said two arrays:

[[3.5 4. 3. ]

[2. 3.5 5. ]]

Click me to see the sample solution

**203.** Write a NumPy program to create a 11x3 array filled with student information (id, class and name) and shuffle the said array rows starting from 3^{rd} to 9^{th}. Go to the editor

Sample Output:

Original array:

[['stident_id' 'Class' 'Name']

['01' 'V' 'Debby Pramod']

['02' 'V' 'Artemiy Ellie']

['03' 'V' 'Baptist Kamal']

['04' 'V' 'Lavanya Davide']

['05' 'V' 'Fulton Antwan']

['06' 'V' 'Euanthe Sandeep']

['07' 'V' 'Endzela Sanda']

['08' 'V' 'Victoire Waman']

['09' 'V' 'Briar Nur']

['10' 'V' 'Rose Lykos']]

Shuffle the said array rows starting from 3rd to 9th

[['stident_id' 'Class' 'Name']

['01' 'V' 'Debby Pramod']

['02' 'V' 'Artemiy Ellie']

['03' 'V' 'Baptist Kamal']

['07' 'V' 'Endzela Sanda']

['04' 'V' 'Lavanya Davide']

['06' 'V' 'Euanthe Sandeep']

['05' 'V' 'Fulton Antwan']

['08' 'V' 'Victoire Waman']

['09' 'V' 'Briar Nur']

['10' 'V' 'Rose Lykos']]

Click me to see the sample solution

**204.** Write a NumPy program to extract all the rows from a given array where a specific column starts with a given character. Go to the editor

Sample Output:

Original array:

[['01' 'V' 'Debby Pramod']

['02' 'V' 'Artemiy Ellie']

['03' 'V' 'Baptist Kamal']

['04' 'V' 'Lavanya Davide']

['05' 'V' 'Fulton Antwan']

['06' 'V' 'Euanthe Sandeep']

['07' 'V' 'Endzela Sanda']

['08' 'V' 'Victoire Waman']

['09' 'V' 'Briar Nur']

['10' 'V' 'Rose Lykos']]

Student name starting with E :

[['06' 'V' 'Euanthe Sandeep']

['07' 'V' 'Endzela Sanda']]

Student id starting with 1 :

[['10' 'V' 'Rose Lykos']]

Click me to see the sample solution

**205.** Write a NumPy program to extract all the rows to compute the student weight from a given array (student information) where a specific column starts with a given character. Go to the editor

Sample Output:

Original array:

[['01' 'V' 'Debby Pramod' '30.21']

['02' 'V' 'Artemiy Ellie' '29.32']

['03' 'V' 'Baptist Kamal' '31.0']

['04' 'V' 'Lavanya Davide' '30.22']

['05' 'V' 'Fulton Antwan' '30.21']

['06' 'V' 'Euanthe Sandeep' '31.0']

['07' 'V' 'Endzela Sanda' '32.0']

['08' 'V' 'Victoire Waman' '29.21']

['09' 'V' 'Briar Nur' '30.0']

['10' 'V' 'Rose Lykos' '32.0']]

Total weight, where student name starting with E

63.0

Total weight, where student name starting with D

30.21

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## Python: Tips of the Day

**Time it:**

timeit library is great for timing Python execution times. Just pass a function in string format to timeit.timeit() method and it will carry out 1 million executions to report the minimum time the code takes.

Its very useful to compare small code pieces and different functions but can be sluggish with big code.

Check out the example below demonstrating the execution time difference between 2 very similar list comprehension methods in Python:

import timeit lst1='''list(range(100))''' lst2='''[i for i in range(100)]''' a=timeit.timeit(lst1) b=timeit.timeit(lst2) print(a, b, sep="------")

Output:

1.9301698543131351------5.389458132907748

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