Contents
- Numpy replace negative with 0: Naive Method
- Numpy replace negative values with zero Using np.clip
- Numpy replace negative with 0 Using np.where
- Replace negative values in an numpy array
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])
