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NumPy: Random Exercises, Practice, Solution

NumPy Random [16 exercises with solution]

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1. Write a NumPy program to generate five random numbers from the normal distribution. Go to the editor
Expected Output:
[-0.43262625 -1.10836787 1.80791413 0.69287463 -0.53742101]
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2. Write a NumPy program to generate six random integers between 10 and 30. Go to the editor
Expected Output:
[20 28 27 17 28 29]
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3. Write a NumPy program to create a 3x3x3 array with random values. Go to the editor
Expected Output:
[[[ 0.48941799 0.58722213 0.43453926]
[ 0.94497547 0.81081709 0.1510409 ]
[ 0.66657127 0.29494755 0.48047144]]
[[ 0.02287253 0.95232614 0.32264936]
[ 0.67009741 0.25458304 0.16290913]
[ 0.15520198 0.86826529 0.9679322 ]]
[[ 0.13503103 0.02042211 0.24683897]
[ 0.97852158 0.22374748 0.10798856]
[ 0.62032646 0.5893892 0.16958144]]]
Click me to see the sample solution

4. Write a NumPy program to create a 5x5 array with random values and find the minimum and maximum values. Go to the editor
Expected Output:
Original Array:
[[ 0.96336355 0.12339131 0.20295196 0.37243578 0.88105252]
[ 0.93228246 0.67470158 0.38103235 0.32242645 0.40610231]
[ 0.3113495 0.31688 0.79189089 0.08676434 0.60829874]
[ 0.30360149 0.94316317 0.98142491 0.77222542 0.51532195]
[ 0.97392305 0.16669609 0.81377917 0.2165645 0.00121611]]
Minimum and Maximum Values:
0.00121610921757 0.981424910368
Click me to see the sample solution

5. Write a NumPy program to create a random 10x4 array and extract the first five rows of the array and store them into a variable. Go to the editor
Sample Output:
Original array:
[[ 0.38593391 0.52823544 0.8994567 0.22097238]
[ 0.16639229 0.74964167 0.58102198 0.2811601 ]
[ 0.56447627 0.42575759 0.71297527 0.91099347]
[ 0.00261548 0.0064798 0.66096109 0.54514293]
[ 0.7216008 0.95815426 0.53370551 0.28116107]
[ 0.16252081 0.26191659 0.40883164 0.60653848]
[ 0.55934457 0.37814126 0.63287808 0.01856616]
[ 0.03788236 0.22705078 0.82024426 0.83019741]
[ 0.31140166 0.43926341 0.38685152 0.92402934]
[ 0.00581032 0.83925377 0.95246879 0.28570894]]
First 5 rows of the above array:
[[ 0.38593391 0.52823544 0.8994567 0.22097238]
[ 0.16639229 0.74964167 0.58102198 0.2811601 ]
[ 0.56447627 0.42575759 0.71297527 0.91099347]
[ 0.00261548 0.0064798 0.66096109 0.54514293]
[ 0.7216008 0.95815426 0.53370551 0.28116107]]

Click me to see the sample solution

6. Write a NumPy program to shuffle numbers between 0 and 10 (inclusive). Go to the editor
Sample Output:
[5 7 9 0 2 3 1 6 8 4]
Same result using permutation():
[6 7 4 5 8 2 3 9 0 1]
Click me to see the sample solution

7. Write a NumPy program to normalize a 3x3 random matrix. Go to the editor
Sample output:
Original Array:
[[ 0.87311805 0.96651849 0.98078621]
[ 0.26407141 0.46784012 0.69947627]
[ 0.20013296 0.75510414 0.26290783]]
After normalization:
[[ 0.86207941 0.98172337 1. ]
[ 0.08190378 0.34292711 0.63964803]
[ 0. 0.71090613 0.08041325]]
Click me to see the sample solution

8. Write a NumPy program to create a random vector of size 10 and sort it. Go to the editor
Expected Output:
Original array:
[ 0.73123073 0.67714015 0.95615347 0.4759837 0.88789818 0.6910404 2
0.59996415 0.26144489 0.51618644 0.89943882]
Sorted array:
[ 0.26144489 0.4759837 0.51618644 0.59996415 0.67714015 0.6910404 2
0.73123073 0.88789818 0.89943882 0.95615347]
Click me to see the sample solution

9. Write a NumPy program to find the nearest value from a given value in an array. Go to the editor
Expected Output:
4.96138509939
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10. Write a NumPy program to check two random arrays are equal or not. Go to the editor
Sample Output:
First array:
[1 0 1 0 1 1]
Second array:
[0 0 1 1 1 0]
Test above two arrays are equal or not!
False
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11. Write a NumPy program to create random vector of size 15 and replace the maximum value by -1. Go to the editor
Sample output:
Original array:
[ 0.34807512 0.76714463 0.40242311 0.5634299 0.84972926 0.92247789
0.93791571 0.5127047 0.50796265 0.50074454 0.26067194 0.07207825
0.04927934 0.95309433 0.14043974]
Maximum value replaced by -1:
[ 0.34807512 0.76714463 0.40242311 0.5634299 0.84972926 0.92247789
0.93791571 0.5127047 0.50796265 0.50074454 0.26067194 0.07207825
0.04927934 -1. 0.14043974]
Click me to see the sample solution

12. Write a NumPy program to find point by point distances of a random vector with shape (10,2) representing coordinates. Go to the editor
Sample output:
[[ 0. 0.09871078 0.42100075 0.75597269 0.52281832 0.13721998
0.1761711 0.28689498 0.42061575 0.61315509]
[ 0.09871078 0. 0.43978557 0.71086596 0.59696144 0.14701023
0.26602812 0.19254215 0.36762701 0.68776127]
.....
[ 0.42061575 0.36762701 0.30691429 0.34395028 0.63326713 0.29974614
0.47787697 0.39922329 0. 0.70954707]
[ 0.61315509 0.68776127 0.4097455 0.85714768 0.09080178 0.55976699
Click me to see the sample solution

13. Write a NumPy program to find the most frequent value in an array. Go to the editor
Sample Output:
Original array:
[6 9 5 1 7 5 1 0 1 5 5 0 8 9 0 7 0 7 6 5 1 1 9 5 3 8 7 9 6 3 4 5 9 7 2 7 0
2 2 6]
Most frequent value in the above array:
5
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14. Write a NumPy program to convert cartesian coordinates to polar coordinates of a random 10x2 matrix representing cartesian coordinates. Go to the editor
Expected Output:
[ 0.89225122 0.68774813 0.20392039 1.22093243 1.24435921 1.00358852
0.37378547 0.8534585 0.31999648 0.567451 ]
[ 1.02751197 1.26964967 0.02567519 0.85386412 0.73152767 0.45822494
1.50634505 1.47389983 0.80818521 0.33001182]
Click me to see the sample solution

15. Write a NumPy program to find the closest value (to a given scalar) in an array. Go to the editor
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 36 37 38 39 40 41 42 43 44 45 46 47 48 49
50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74
75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99]
Value to compare:
34.99062268928913
35
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16. Write a NumPy program to get the n largest values of an array. Go to the editor
Sample output:
Original array:
[0 1 2 3 4 5 6 7 8 9]
[9]
Click me to see the sample solution

Python Code Editor:

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Python: Tips of the Day

Python: Annotated Assignment Statement

This might not seem as impressive as some other tricks but it's a new syntax that was introduced to Python in recent years and just good to be aware of.

Annotated assignments allow the coder to leave type hints in the code. These don't have any enforcing power at least not yet. It's still nice to be able to imply some type hints and definitely offers more options than only being able to comment regarding expected types of variables.

day: str = 'Monday'
print(day)
lst: list = [1,2,3,4]
print(lst)

Output:

Monday
[1, 2, 3, 4]

Or the same thing in a shorter way:

day= 'Monday' #str
print(day)
lst= [1,2,3,4] # list
print(lst)

Output:

Monday
[1, 2, 3, 4]