Given numpy array, the goal is to replace negative values with zeros in numpy array. Let’s check up some examples of this issue.
Numpy replace negative with 0: Naive Method
# Python code to demonstrate
# to replace negative value with 0
import numpy as np
ini_array1 = np.array([1, 2, -3, 4, -5, -6])
# printing initial arrays
print("initial array", ini_array1)
# code to replace all negative value with 0
ini_array1[ini_array1<0] = 0
# printing result
print("New resulting array: ", ini_array1)
Output:
initial array [ 1 2 -3 4 -5 -6] New resulting array: [1 2 0 4 0 0]
Numpy replace negative values with zero Using np.clip
# Python code to demonstrate
# to replace negative values with 0
import numpy as np
# supposing maxx value array can hold
maxx = 1000
ini_array1 = np.array([1, 2, -3, 4, -5, -6])
# printing initial arrays
print("initial array", ini_array1)
# code to replace all negative value with 0
result = np.clip(ini_array1, 0, 1000)
# printing result
print("New resulting array: ", result)
Output:
initial array [ 1 2 -3 4 -5 -6] New resulting array: [1 2 0 4 0 0]
Numpy replace negative with 0 Using np.where
# Python code to demonstrate
# to replace negative values with 0
import numpy as np
ini_array1 = np.array([1, 2, -3, 4, -5, -6])
# printing initial arrays
print("initial array", ini_array1)
# code to replace all negative value with 0
result = np.where(ini_array1<0, 0, ini_array1)
# printing result
print("New resulting array: ", result)
Output:
initial array [ 1 2 -3 4 -5 -6] New resulting array: [1 2 0 4 0 0]
Method #4: Comparing the given array with an array of zeros and write in the maximum value from the two arrays as the output
# Python code to demonstrate
# to replace negative values with 0
import numpy as np
ini_array1 = np.array([1, 2, -3, 4, -5, -6])
# printing initial arrays
print("initial array", ini_array1)
# Creating a array of 0
zero_array = np.zeros(ini_array1.shape, dtype=ini_array1.dtype)
print("Zero array", zero_array)
# code to replace all negative value with 0
ini_array2 = np.maximum(ini_array1, zero_array)
# printing result
print("New resulting array: ", ini_array2)
Output:
initial array [ 1 2 -3 4 -5 -6] Zero array [0 0 0 0 0 0] New resulting array: [1 2 0 4 0 0]
Replace negative values in an numpy array
StackOverflow question
Is there a simple way of replacing all negative values in an array with 0?
I’m having a complete block on how to do it using a NumPy array.
E.g.
a = array([1, 2, 3, -4, 5])
I need to return
[1, 2, 3, 0, 5]
a < 0 gives:
[False, False, False, True, False]
This is where I’m stuck - how to use this array to modify the original array.
Answer:
In [4]: a[a < 0] = 0 In [5]: a Out[5]: array([1, 2, 3, 0, 5])