NumPy: Create a two-dimensional array of specified format

NumPy: Basic Exercise-46 with Solution

Write a NumPy program to create a two-dimensional array of a specified format.

This problem involves writing a NumPy program to generate a two-dimensional array with a specified format, which could include specific numerical values, patterns, or data distributions. The task requires utilizing NumPy's array creation functions to construct the array according to the desired format. By specifying the dimensions, content, and structure of the array, the program effectively creates a customized two-dimensional array suitable for various computational and analytical purposes.

Sample format:

[[  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  99 100]
 [101 102 103 104 105 106 107 108 109 110]
 [111 112 113 114 115 116 117 118 119 120]
 [121 122 123 124 125 126 127 128 129 130]
 [131 132 133 134 135 136 137 138 139 140]
 [141 142 143 144 145 146 147 148 149 150]]

Sample Solution :

Python Code :

# Importing the NumPy library with an alias 'np'
import numpy as np   

# Printing a message indicating the creation of an array of shape (15,10)
print("Create an array of shape (15,10):") 

# Printing a message indicating Command-1 and displaying the result
print("Command-1")
print(np.arange(1, 151).reshape(15, 10)) 

# Printing a message indicating Command-2 and displaying the result
print("\nCommand-2")
print(np.arange(1, 151).reshape(-1, 10)) 

# Printing a message indicating Command-3 and displaying the result
print("\nCommand-3")
print(np.arange(1, 151).reshape(15, -1)) 

Output:

Create an array of shape (15,10):
Command-1
[[  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  99 100]
 [101 102 103 104 105 106 107 108 109 110]
 [111 112 113 114 115 116 117 118 119 120]
 [121 122 123 124 125 126 127 128 129 130]
 [131 132 133 134 135 136 137 138 139 140]
 [141 142 143 144 145 146 147 148 149 150]]

Command-2
[[  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  99 100]
 [101 102 103 104 105 106 107 108 109 110]
 [111 112 113 114 115 116 117 118 119 120]
 [121 122 123 124 125 126 127 128 129 130]
 [131 132 133 134 135 136 137 138 139 140]
 [141 142 143 144 145 146 147 148 149 150]]

Command-3
[[  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  99 100]
 [101 102 103 104 105 106 107 108 109 110]
 [111 112 113 114 115 116 117 118 119 120]
 [121 122 123 124 125 126 127 128 129 130]
 [131 132 133 134 135 136 137 138 139 140]
 [141 142 143 144 145 146 147 148 149 150]]

Explanation:

In the above code –

print(np.arange(1, 151).reshape(15, 10)): This statement creates a NumPy array with integers from 1 (inclusive) to 151 (exclusive), i.e., integers from 1 to 150, and reshapes it into a 15x10 matrix (15 rows and 10 columns). A copy of the results is printed.

print(np.arange(1, 151).reshape(-1, 10)): This statement creates a NumPy array with integers from 1 to 150, similar to the first example. It then reshapes it into a matrix with 10 columns, and the number of rows is inferred automatically (indicated by -1). In this case, the inferred number of rows is 15. A copy of the results is printed.

print(np.arange(1, 151).reshape(15, -1)): This statement creates a NumPy array with integers from 1 to 150. It then reshapes it into a matrix with 15 rows, and the number of columns is inferred automatically (indicated by -1). In this case, the inferred number of columns is 10. A copy of the results is printed.

Python-Numpy Code Editor:

Previous: NumPy program to create one-dimensional array of single, two and three digit numbers.
Next: NumPy program to create a one dimensional array of forty pseudo-randomly generated values. Select random numbers from a uniform distribution between 0 and 1.