[Term Entry] Python - NumPy Random module: .rand()

content/numpy/concepts/random-module/terms/rand/rand.md

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+---
+Title: '.rand()'
+Description: 'Returns an array of the given shape with random samples from a uniform distribution over [0, 1).'
+Subjects:
+  - 'Computer Science'
+  - 'Data Science'
+Tags:
+  - 'Arrays'
+  - 'Functions'
+  - 'Math'
+  - 'NumPy'
+CatalogContent:
+  - 'learn-python-3'
+  - 'paths/computer-science'
+---
+
+The **`.rand()`** function from the NumPy library returns an array of a specified shape filled with uniformly distributed random values between 0 and 1. The shape of the output array is determined by the parameters passed to the function.
+
+This function is commonly used for creating random arrays in applications like machine learning and simulations.
+
+## Syntax
+
+```pseudo
+numpy.random.rand(d0, d1, ..., dn)
+```
+
+**Parameters:**
+
+- `d0, d1, ..., dn` (int, optional): Dimensions of the returned array. Each parameter represents the size along a particular axis.
+
+**Return value:**
+
+An array ([`ndarray`](https://www.codecademy.com/resources/docs/numpy/ndarray)) of shape (`d0, d1, ..., dn`) filled with random floats from a uniform distribution over [0, 1).
+
+## Example
+
+The following examples demonstrate the use of `.rand()` from numpy library:
+
+```py
+import numpy as np
+
+# Using .rand() to generate a single float value
+single_float = np.random.rand()
+print("This is a single float:", single_float, "\n")
+
+# Using .rand() to generate a 1D array with 5 elements
+oneD_array = np.random.rand(5)
+print("This is a 1D array with 5 elements:", oneD_array, "\n")
+
+# Using .rand() to generate a 2D array with shape (3, 4)
+twoD_array = np.random.rand(3, 4)
+print("This is a 2D array with shape (3, 4):", twoD_array, "\n")
+
+# Using .rand() to generate a 3D array with shape (2, 4, 3)
+fourD_array = np.random.rand(2, 4, 3)
+print("This is a 3D array with shape (2, 4, 3):", fourD_array, "\n")
+```
+
+The possible ouput for this code can be:
+
+```shell
+This is a single float: 0.062282333140694646
+
+This is a 1D array: [0.26135751 0.68792718 0.29413907 0.96249664 0.96284554]
+
+This is a 2D array with shape (3, 4): [[0.43097673 0.1741973  0.92504336 0.70587898]
+ [0.04921928 0.55717071 0.66223492 0.52897239]
+ [0.43088071 0.72260989 0.77430222 0.91549911]]
+
+This is a 4D array with shape (2, 4, 3): [[[0.66207525 0.72505789 0.56002624]
+  [0.49060286 0.68176017 0.5740969 ]
+  [0.60655012 0.83349518 0.85648538]
+  [0.18412521 0.29999511 0.89179013]]
+
+ [[0.29378119 0.08597027 0.68488609]
+  [0.95905169 0.24037647 0.21941708]
+  [0.17337005 0.86617885 0.45531762]
+  [0.06081413 0.08813921 0.34166149]]]
+```
+
+> **Note:** The output of `np.random.rand()` will change each time because it generates pseudo-random numbers based on the system's internal state, which varies with each execution.
+
+## Codebyte Example
+
+The following codebyte is an example of the `.rand()` in use to generate different dimensional arrays:
+
+```codebyte/python
+import numpy as np
+import random
+
+# Create a float using .rand()
+single_float = np.random.rand()
+
+print("The float made using numpy.random.rand() is", single_float, "\n")
+
+# Create a random integer between 1 and 10
+t = random.randint(1, 10)
+
+# Create a random integer between 1 and 5
+s = random.randint(1, 5)
+
+# Create a one-dimensional array with a random number (between 1 and 10) of elements
+one_d_array = np.random.rand(t)
+
+print('The 1-dimensional array using numpy.random.rand() is', one_d_array, "\n")
+
+# Create a five-dimensional array with random values
+five_d_array = np.random.rand(s, 4, 6, 7, 1)
+
+print("The 5-dimensional array using numpy.random.rand() is", five_d_array, "\n")
+```