The all() function in Python is simply used to check if all the elements of an array along a given axis evaluate to True.
numpy.all(a, axis=None, out=None, keepdims=<no value>, *, where=<no value>)
The all() function takes a mandatory function a which represents the input array or objects that can be converted to an array.
The all() function takes the following optional parameter values:
axis: The represents the axis or axes along which a logical AND reduction is perfromed. The default value is (axis = None) and when negative, it counts from the last to the first axis.out: This represents an alternate output array in which to place to the result. It must have the same shape as the expected output array.keepdims: If this is set to True, axes which are reduced are left in the result as dimensions with size one.where: This represents elements to include in checking for all True values.The all() function returns a boolean value or array.
import numpy as np# creating an arraymyarray = np.arange(6) + 1# calling the numpy.all() functionnewarray = np.all(myarray)# printing the arrayprint(newarray)
numpy module.myarray.all() function on the array myarray. The result is assigned to a new variable, newarray.newarray.