python-scipyHow can I use Python Numpy to select elements from an array based on multiple conditions?
To select elements from an array based on multiple conditions using Python Numpy, we can use the np.where()
function. This function takes a condition as an argument, and returns the indices of the elements in the array that satisfy the condition.
For example:
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
indices = np.where((arr > 2) & (arr < 8))
print(indices)
This will output (array([0, 1, 1, 2], dtype=int64), array([1, 0, 1, 2], dtype=int64))
The np.where()
function can take multiple conditions, which are evaluated using the bitwise operators &
(and) and |
(or).
The parts of the code are:
np.where()
: function used to select elements from an array based on multiple conditionsarr > 2
: condition to select elements greater than 2arr < 8
: condition to select elements less than 8&
: bitwise operator to combine the two conditions
Helpful links
More of Python Scipy
- How do I create a numpy array of zeros using Python?
- How do I use Python Numpy to read and write Excel (.xlsx) files?
- How do I use Scipy zeros in Python?
- How can I check if a certain version of Python is compatible with SciPy?
- How to use Python, XML-RPC, and NumPy together?
- How do I uninstall Python Scipy?
- How can I use Python and SciPy to perform a Short-Time Fourier Transform?
- How do I calculate a Jacobian matrix using Python and NumPy?
- How do I create a 2D array of zeros using Python and NumPy?
- How can I use RK45 with Python and SciPy?
See more codes...