Binarize Data

Data Wrangling

Difficulty: 2 | Problem written by mesakarghm
Problem reported in interviews at


Data Binarization is the process of converting continuous or categorical data to binary form using a threshold. Write a function binarize(arr,thresh) which converts the input array (1D list) to binary form (1D numpy array) using the given threshold. Data points above the threshold should be converted to "1", otherwise they should be converted to "0".


Sample Input:
<class 'list'>
arr: [100, 50, 10, 9]
<class 'int'>
threshold: 25

Expected Output:
<class 'numpy.ndarray'>
[1 1 0 0]

This is a premium problem, to view more details of this problem please sign up for MLPro Premium. MLPro premium offers access to actual machine learning and data science interview questions and coding challenges commonly asked at tech companies all over the world

MLPro Premium also allows you to access all our high quality MCQs which are not available on the free tier.

Not able to solve a problem? MLPro premium brings you access to solutions for all problems available on MLPro

Get access to Premium only exclusive educational content available to only Premium users.

Have an issue, the MLPro support team is available 24X7 to Premium users.

This is a premium feature.
To access this and other such features, click on upgrade below.

Log in to post a comment

Jump to comment-78
rafi • 7¬†months, 2¬†weeks ago


We can use NumPy to manipulate the array.

import numpy as np

# Please do not change the below function name and parameters
def binarize(arr,threshold):
    arr = np.array(arr)
    bin = (arr>threshold).astype(np.int_)
    return bin



Input Test Case

Please enter only one test case at a time
numpy has been already imported as np (import numpy as np)