numpy.floor() is used to return the floor value of the elements of an array. The floor value of any given scalar value x is the largest integer value, such that
i <= x. For example, the floor value for 2.3 will be 2.
Below we have a basic syntax to use this function and it is as follows:
The parameter named array is used to denote the array whose floor value needs to be calculated.
This method will return an array that contains floor values only.
Note: In some spreadsheet programs value will be calculated through “floor-towards-zero” way that means floor(-2.8) == -2. But in case of Numpy, the definition of floor is the opposite, floor(-2.8) == -3, so we always pick the closest lower integer value to ind the floor.
Now its time to cover a few examples in order to understand this example.
Below we have a code snippet for the example. Let us take a look at it:
import numpy as np a = [0.23,-1.7,1.34,-2.334] print("The array is :",a) y = np.floor(a) print("After applying the floor() method:",y)
The array is : [0.23, -1.7, 1.34, -2.334] After applying the floor() method: [ 0. -2. 1. -3.]
Now here is another example for the
import numpy as np input_arr = [1.23,0.22,-0.111,-2.555,-3.86,5.0,6.9] print("The Input array is:") print(input_arr) z = np.floor(input_arr) print("The output array is:") print(z)
The Input array is: [1.23, 0.22, -0.111, -2.555, -3.86, 5.0, 6.9] The output array is: [ 1. 0. -1. -3. -4. 5. 6.]