Let’s check how to rank values in a Numpy array by axis.
Sometimes values do not matter so much. You may want to know the order.
Ranking with argsort
See how to rank values using the argsort Numpy function.
import numpy as np my_array = np.array([[1, 56, 55, 15], [5, 4, 33, 53], [3, 6, 7, 19]]) sorted_array = np.argsort(my_array, axis=0) print(f"These are ranks of array values: \n {sorted_array}")
As you can see, there are ranks given for the values in your array. You can work on them further.
Ranking over another axis
Do you want to rank it differently? No problem. See:
import numpy as np my_array = np.array([[1, 56, 55, 15], [5, 4, 33, 53], [3, 6, 7, 19]]) sorted_array = np.argsort(my_array, axis=1) print(f"These are ranks of array values: \n {sorted_array}")
By changing the axis parameter to 1, the ranking is performed within each row rather than each column.