Examples of how to randomly select rows of an array in python with numpy:
Create an array with numpy
Let create the following array:
>>> import numpy as np
>>> data = np.arange(80).reshape((8, 10))
>>> data
array([[ 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]])
\begin{equation}
data = \left( \begin{array}{ccc}
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
\end{array}\right)
\end{equation}
Using the function shuffle
To randomly select rows of the array, a solution is to first shuffle() the array:
>>> np.random.shuffle(data)
>>> data
array([[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
[30, 31, 32, 33, 34, 35, 36, 37, 38, 39],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19],
[70, 71, 72, 73, 74, 75, 76, 77, 78, 79]])
and to slice the n first rows, example with n = 4,
>>> data = data[:4,:]
>>> data
array([[50, 51, 52, 53, 54, 55, 56, 57, 58, 59],
[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69]])
\begin{equation}
data = \left( \begin{array}{ccc}
50 & 51 & 52 & 53 & 54 & 55 & 56 & 57 & 58 & 59 \\
0 & 1 & 2 & 3 & 4 & 5 & 6 & 7 & 8 & 9 \\
40 & 41 & 42 & 43 & 44 & 45 & 46 & 47 & 48 & 49 \\
60 & 61 & 62 & 63 & 64 & 65 & 66 & 67 & 68 & 69
\end{array}\right)
\end{equation}
Note: to remove rows where a condition is true (see), we can do:
>>> data = data[~(data[:,3] > 50)]
>>> data
array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[40, 41, 42, 43, 44, 45, 46, 47, 48, 49]])
Create a list of random integers
Another option is to create a list of random integers:
>>> data = np.arange(80).reshape((8, 10))
>>> data
array([[ 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]])
>>> import random
>>> rows_id = random.sample(range(0,data.shape[1]-1), 4)
>>> rows_id
[4, 6, 2, 3]
>>> data = data[rows_id,:]
>>> data
array([[40, 41, 42, 43, 44, 45, 46, 47, 48, 49],
[60, 61, 62, 63, 64, 65, 66, 67, 68, 69],
[20, 21, 22, 23, 24, 25, 26, 27, 28, 29],
[30, 31, 32, 33, 34, 35, 36, 37, 38, 39]])
References
Links | Site |
---|---|
numpy.random.shuffle | Scipy Doc |
Create numpy array with random elements from list | stackoverflow |
randomly selecting items from an array python | stackoverflow |
Select cells randomly from NumPy array - without replacement | stackoverflow |
How to truncate matrix using NumPy (Python) | stackoverflow |
How to truncate the values of a 2D numpy array | stackoverflow |
numpy.delete | stackoverflow |
Python delete row in numpy array | stackoverflow |