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Python | Filter out integers from float numpy array
  • Last Updated : 15 Mar, 2019

Given a numpy array, the task is to filter out integers from an array containing float and integers. Let’s see few methods to solve a given task.

Method #1 : Using astype(int)

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# Python code to demonstrate 
# filtering integers from numpy array
# containing integers and float
  
import numpy as np
  
# initialising array
ini_array = np.array([1.0, 1.2, 2.2, 2.0, 3.0, 2.0])
  
# printing initial array
print ("initial array : ", str(ini_array))
  
# filtering integers
result = ini_array[ini_array != ini_array.astype(int)]
  
# printig resultant
print ("final array", result)

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Output:

initial array :  [ 1.   1.2  2.2  2.   3.   2. ]
final array [ 1.2  2.2]

 
Method #2: Using np.equal() and np.mod()

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# Python code to demonstrate 
# filtering integers from numpy array
# containing integers and float
  
import numpy as np
  
# initialising array
ini_array = np.array([1.0, 1.2, 2.2, 2.0, 3.0, 2.0])
  
# printing initial array
print ("initial array : ", str(ini_array))
  
# filtering integers
result = ini_array[~np.equal(np.mod(ini_array, 1), 0)]
  
# printing resultant
print ("final array : ", str(result))

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Output:



initial array :  [ 1.   1.2  2.2  2.   3.   2. ]
final array :  [ 1.2  2.2]

 
Method #3: Using np.isclose()

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# Python code to demonstrate 
# filtering integers from numpy array
# containing integers and float
  
import numpy as np
  
# initialising array
ini_array = np.array([1.0, 1.2, 2.2, 2.0, 3.0, 2.0])
  
# printing initial array
print ("initial array : ", str(ini_array))
  
# filtering integers
mask = np.isclose(ini_array, ini_array.astype(int))
result = ini_array[~mask]
  
# printing resultant
print ("final array : ", str(result))

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Output:

initial array :  [ 1.   1.2  2.2  2.   3.   2. ]
final array :  [ 1.2  2.2]

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