In this tutorial, we will look at how to count the values in a Numpy array that are between a given range, let’s say from
end (both inclusive) with the help of some examples
Steps to get the count of all the values between a range in Numpy
In general, to find the count of values in a Numpy array that satisfy the given condition, you can –
📚 Discover Online Data Science Courses & Programs (Enroll for Free)
- Harvard University Data Science: Learn R Basics for Data Science
- Standford University Data Science: Introduction to Machine Learning
- UC Davis Data Science: Learn SQL Basics for Data Science
- IBM Data Science: Professional Certificate in Data Science
- IBM Data Analysis: Professional Certificate in Data Analytics
- Google Data Analysis: Professional Certificate in Data Analytics
- IBM Data Science: Professional Certificate in Python Data Science
- IBM Data Engineering Fundamentals: Python Basics for Data Science
- Harvard University Learning Python for Data Science: Introduction to Data Science with Python
- Harvard University Computer Science Courses: Using Python for Research
- IBM Python Data Science: Visualizing Data with Python
- DeepLearning.AI Data Science and Machine Learning: Deep Learning Specialization
- UC San Diego Data Science: Python for Data Science
- UC San Diego Data Science: Probability and Statistics in Data Science using Python
- Google Data Analysis: Professional Certificate in Advanced Data Analytics
- MIT Statistics and Data Science: Machine Learning with Python - from Linear Models to Deep Learning
- MIT Statistics and Data Science: MicroMasters® Program in Statistics and Data Science
🔎 Find Data Science Programs 👨💻 111,889 already enrolled
Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers.
- Use boolean indexing to filter the array for only the values that satisfy the condition.
- Calculate the length of the filtered array from step 1.
Thus, first, filter the Numpy array to contain only the values that lie between the specified range and then find its length to get the required count.
Let’s now look at a step-by-step example.
Step 1 – Create a Numpy array
First, we will create a Numpy array that we will be using throughout this tutorial.
import numpy as np # create a numpy array ar = np.array([1, 2, 3, 5, 8, 9]) # display the array print(ar)
[1 2 3 5 8 9]
Here, we used the
numpy.array() function to create a one-dimensional Numpy array containing some numbers.
Step 2 – Filter the array using a boolean expression
To get all the values from a Numpy array that lie in a given range, filter the array using boolean indexing.
First, we will specify our boolean expression,
(ar >= start) & (ar <= end) and then use the boolean array resulting from this expression to filter our original array.
For example, let’s get all the values in the above array that lie between the range 2 to 6.
# values in array between the range [2, 6] ar_filtered = ar[(ar >= 2) & (ar <= 6)] print(ar_filtered)
[2 3 5]
We get all the values in the array
ar that lie in the range [2, 6].
Step 3 – Get the length of the filtered array
To get the count of values that satisfy the given condition (whether it lies in a given range or not) find the length of the resulting filtered array from step 2 using the Python built-in
# length of the filtered array print(len(ar_filtered))
We get the count of values in the array
ar that lie between the range 2 to 6 as 3.
We can combine the code from the last two steps into a single line of code.
# count of values in array between the range [2, 6] print(len(ar[(ar >= 2) & (ar <= 6)]))
We get the same result as above and we removed the extra variable
In this tutorial, we looked at how to count the values in a Numpy array that lie in a given range. Note that in this method we’re not counting the unique elements that are in that range, rather we’re counting all the values in an array that are in the given range (which may include duplicates depending on the array).
You might also be interested in –
- Numpy Array – Get All Values Greater than a Given Value
- Get unique values and counts in a numpy array
- Get the Most Frequent Value in Numpy Array
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.