Print the full NumPy array without truncation in Python

In this article, we will see how we can print a full NumPy array without truncation in Python. Truncation means making something shorter. The Python interpreter automatically truncates large NumPy arrays when displaying them in the shell, noting that certain elements are omitted in the textual information of the collection with the three dots ‘…’. To get around this, we employ a few strategies, which we’ll go over below.

Printing the array with Truncation in Python:

import numpy as np
array = np.arange(1001)
print(array)

Output:

[ 0 1 2 ... 998 999 1000]

To solve this issue we will employ some methods below:

Print the full NumPy array without truncation using numpy.set_printoptions()

The np.set_printoptions function has an attribute called  threshold=np.inf or threshold=sys.maxsize. This allows us the users to print the array without any truncation.

 Code to Print the full NumPy array without truncation:

# Importing required modules
import numpy as np
import sys

# Creating a 1-D array with 200 values
array = np.arange(201)

# Printing all values of array without truncation
np.set_printoptions(threshold=sys.maxsize)
print(array)

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
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
144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161
162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179
180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197
198 199 200]

Print the full NumPy array without truncation using Using threshold = np.inf

Here, the threshold is set to np.inf, the floating-point equivalent of infinity.

# Importing important modules
import numpy as np
import sys

# Creating a 1-D array with 100 values
array = np.arange(101)

# this will gives us truncation free output.
np.set_printoptions(threshold=np.inf)
print(array)

It will print the array.

With this example, we have completed our tutorial. Learn, Vectorized Operations in NumPy with examples

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