In this article, we will see two different methods on how to randomly select rows of an array in Python with NumPy. Let’s see different methods by which we can select random rows of an array:
Method 1: We will be using the function shuffle(). The shuffle() function shuffles the rows of an array randomly and then we will display a random row of the 2D array.
Python3
# import modules import random import numpy as np # create 2D array data = np.arange(50).reshape((5, 10)) # display original array print("Array:") print(data) # row manipulation np.random.shuffle(data) # display random rows print("\nRandom row:") rows = data[:1, :] print(rows) |
Output:
Method 2: First create an array, then apply the sample() method to it and display a single row.
Python3
# import modules import random import numpy as np # create 2D array data = np.arange(50).reshape((5, 10)) # display original array print("Array:") print(data) # row manipulation rows_id = random.sample(range(0, data.shape[1]-1), 1) # display random rows print("\nRandom row:") row = data[rows_id, :] print(row) |
Output:
Method 3: We will be using the function choice(). The choices() method returns multiple random elements from the list with replacement.
Now lets, select rows from the list of random integers that we have created.
Python3
# import modules import random import numpy as np # create 2D array data = np.arange(50).reshape((5, 10)) # display original array print("Array:") print(data) # row manipulation number_of_rows = data.shape[0] random_indices = np.random.choice(number_of_rows, size=1, replace=False) # display random rows print("\nRandom row:") row = data[random_indices, :] print(row) |
Output:
