https://www.statology.org/qualitative-vs-quantitative-variables/
https://www.statology.org/numpy-swap-rows/
How to Swap Two Rows in a NumPy Array (With Example)
You can use the following basic syntax to swap two rows in a NumPy array:
some_array[[0, 3]] = some_array[[3, 0]]
This particular example will swap the first and fourth rows in the NumPy array called some_array.
All other rows will remain in their original positions.
The following example shows how to use this syntax in practice.
Example: Swap Two Rows in NumPy Array
Suppose we have the following NumPy array:
import numpy as np
create NumPy array
some_array = np.array([[1, 1, 2], [3, 3, 7], [4, 3, 1], [9, 9, 5], [6, 7, 7]])
view NumPy array
print(some_array)
[[1 1 2]
[3 3 7]
[4 3 1]
[9 9 5]
[6 7 7]]
We can use the following syntax to swap the first and fourth rows in the NumPy array:
swap rows 1 and 4
some_array[[0, 3]] = some_array[[3, 0]]
view updated NumPy array
print(some_array)
[[9 9 5]
[3 3 7]
[4 3 1]
[1 1 2]
[6 7 7]]
Notice that the first and fourth rows have been swapped.
All other rows remained in their original positions.
Note that some_array[[0, 3]] is shorthand for some_array[[0, 3], :] so we could also use the following syntax to get the same results:
swap rows 1 and 4
some_array[[0, 3], :] = some_array[[3, 0], :]
view updated NumPy array
print(some_array)
[[9 9 5]
[3 3 7]
[4 3 1]
[1 1 2]
[6 7 7]]
Notice that the first and fourth rows have been swapped.
This result matches the result from using the shorthand notation in the previous example.
Feel free to use whichever notation you prefer to swap two rows in a given NumPy array.
Additional Resources
The following tutorials explain how to perform other common tasks in NumPy:
- Statistics Applied Example Array NumPystatistics applied example array indices values array numpy ndarray flatten numpy array numpy array 数组python numpy array applied statistics automatically discovering categories statistics mathematical statistics stat 2001 logic uncertainties statistics certainty