In this tutorial, we will look at how to count the positive values in a Numpy array with the help of some examples.
Steps to get the count of positive values in a Numpy array
In general, to find the count of values in a Numpy array that satisfy the given condition, you can –
- 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 positive values 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([-2, -1, 0, 1, 2, 3]) # display the array print(ar)
Output:
[-2 -1 0 1 2 3]
Here, we used the numpy.array()
function to create a one-dimensional Numpy array containing some numbers. You can see that the array contains some positive and negative numbers (along with a zero).
Step 2 – Filter the array using a boolean expression
To get all the values from a Numpy array that are positive, filter the array using boolean indexing.
Introductory ⭐
- 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
Intermediate ⭐⭐⭐
- 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
Advanced ⭐⭐⭐⭐⭐
- 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.
First, we will specify our boolean expression, ar > 0
and then use the boolean array resulting from this expression to filter our original array.
Let’s get all the positive values in the above array.
# positive values in the array ar ar_filtered = ar[ar > 0] print(ar_filtered)
Output:
[1 2 3]
We get all the values in the array ar
that are positive (greater than zero).
Step 3 – Get the length of the filtered array
To get the count of values that satisfy the given condition (whether it’s positive or not) find the length of the resulting filtered array from step 2 using the Python built-in len()
function.
# length of the filtered array print(len(ar_filtered))
Output:
3
We get the count of positive values in the array ar
as 3.
We can combine the code from the last two steps into a single line of code.
# count of positive values in the array ar print(len(ar[ar > 0]))
Output:
3
We get the same result as above and we removed the extra variable ar_filtered
.
In this tutorial, we looked at how to count the positive values in a Numpy array. Note that in this method we’re not counting unique elements that are positive, rather we’re counting all values in an array that are positive (which may include duplicates depending on the array).
You might also be interested in –
- Numpy – Make All Positive Values Zero in Array
- Numpy Array – Get All Values Greater than a Given Value
- Get unique values and counts in a numpy array
- Numpy – Make All Positive Values Negative
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.