The Python numpy random randn function returns the array of random numbers from the standard normal distribution and the syntax is
numpy.random.randn(d0, d1, d2, d3,……, dn)
d0, d1, d2, d3,……, dn argument values are optional, and they specify the array dimension. If we provide the positive arguments, the Python numpy random randn function generates a given shape filled with random float values.
Python numpy random randn Examples
If you don’t provide any argument value, then the random randn returns a float value. Otherwise, this function returns a ndarray. In this example, we use this function without any arguments.
import numpy as np randnArr1 = np.random.randn() print(randnArr1) print() randnArr2 = np.random.randn() print(randnArr2)
-0.1190630720571025
0.13108588886851796
Python numpy random randn 1D Array
Here, the function with argument (5) creates a one-dimensional array and fills them with arbitrarily numbers.
import numpy as np randnOneDArr1 = np.random.randn(5) print(randnOneDArr1) print() randnOneDArr2 = np.random.randn(8) print(randnOneDArr2)
[-0.15532315 1.48066508 0.02134949 1.42327666 0.35529594]
[-1.08493387 -0.33618251 1.6513366 -0.76712552 0.20014333 -0.09537157
0.12968054 -1.06886917]
2D randn random array
import numpy as np randnTwoDArr1 = np.random.randn(2, 3) print(randnTwoDArr1) print() randnTwoDArr2 = np.random.randn(4, 5) print(randnTwoDArr2)
[[ 1.16499735 -0.29089086 -0.61637367]
[-1.33852303 -1.55360179 -0.57502968]]
[[-1.19540849 -1.26507447 0.42922849 -0.99128182 -0.56647817]
[-0.18800185 -1.3729178 -0.06733882 0.21002692 0.97676689]
[-0.07614783 1.66854604 1.43727936 1.10420558 -0.47618305]
[-0.84303037 0.80345969 0.43075844 -0.52133616 0.39946079]]
3D Array
import numpy as np randnThreeDArr1 = np.random.randn(2, 2, 3) print(randnThreeDArr1) print() randnThreeDArr2 = np.random.randn(2, 4, 5) print(randnThreeDArr2)
Multidimensional random randn Array
import numpy as np randnThreeDArr1 = np.random.randn(2, 2, 2, 3) print(randnThreeDArr1) print() randnThreeDArr2 = np.random.randn(2, 2, 2, 2, 4) print(randnThreeDArr2)
[[[[-0.49003723 0.10538309 1.00878589]
[-1.04090049 -0.12316203 -2.71174546]]
[[ 0.64973719 0.7905445 -2.21885022]
[-0.42551294 0.07225683 0.06877539]]]
[[[-1.31479185 -0.02534445 0.40838083]
[-1.41941676 1.4174154 1.00272178]]
[[ 1.67533883 -0.73425059 0.4134018 ]
[ 1.0205856 0.81890094 0.70149338]]]]
[[[[[-0.21434075 -0.34164547 -0.00858992 -0.49217858]
[ 1.0692015 -0.45626313 -0.74388692 0.04669171]]
[[ 0.5586004 0.4855915 -1.01220602 1.19120821]
[-0.16605316 1.14090238 0.03363894 -1.11966274]]]
[[[ 1.74147131 -0.59825137 -1.10534603 -0.62323573]
[ 0.38333497 0.24989126 -0.43793776 0.38728504]]
[[-0.9094845 0.50144625 -0.03183788 1.51701865]
[ 0.72316509 -0.3764924 -0.79577108 -0.1124155 ]]]]
[[[[-0.06678042 -0.71614296 -0.56540373 -0.23460517]
[-1.43545586 0.19400586 -0.46936663 0.22060458]]
[[-1.63621087 -1.04987423 -0.92225825 -0.10737135]
[-1.31863337 1.39154389 -0.56283176 1.20248983]]]
[[[ 1.88742062 0.69761658 0.01897559 0.46728448]
[ 0.75501117 1.08072768 0.66426271 0.13344399]]
[[-1.36858917 1.48854343 0.4055712 -0.52813708]
[-0.45967513 -0.64985973 -0.42966048 -0.56245859]]]]]
Apart from this, we can also perform calculations or Python arithmetic operations on it.
import numpy as np randnThreeDArr1 = np.random.randn(2, 3) print(randnThreeDArr1) print("\nrandn random array multiplies with 12 = \n", randnThreeDArr1 * 12) print("\n2D random randn array multiplies with 15 and added 4 to it") print(np.random.randn(2, 3) * 15 + 4) print("\n3D random randn array multiplies with 9 and added 11 to it") print(np.random.randn(2, 2, 3) * 9 + 11)
[[-0.37226814 1.45008532 1.23092693]
[ 0.56230156 -0.47328258 -0.36321147]]
randn random array multiplies with 12 =
[[-4.46721768 17.4010238 14.77112321]
[ 6.74761877 -5.67939092 -4.35853763]]
2D random randn array multiplies with 15 and added 4 to it
[[ 3.69442594 -2.0569281 10.45519936]
[ 22.77077114 -12.65088561 -14.92586724]]
3D random randn array multiplies with 9 and added 11 to it
[[[-1.22722572 8.52319722 1.47347351]
[ 0.40692321 7.12153801 3.69733377]]
[[21.83366764 11.02923414 7.50767092]
[ 6.0678307 -2.95467098 23.18938078]]]