Numpy – Count Negative Values in an Array

In this tutorial, we will look at how to count the negative values in a Numpy array with the help of some examples.

Steps to get the count of negative values in a Numpy array

In general, to find the count of values in a Numpy array that satisfy the given condition, you can –

1. Use boolean indexing to filter the array for only the values that satisfy the condition.
2. Calculate the length of the filtered array from step 1.

Thus, first, filter the Numpy array to contain only the negative 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 negative, filter the array using boolean indexing.

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 negative values in the above array.

# negative values in the array ar
ar_filtered = ar[ar < 0]
print(ar_filtered)

Output:

[-2 -1]

We get all the values in the array ar that are negative (less 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 negative 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:

2

We get the count of negative values in the array ar as 2.

We can combine the code from the last two steps into a single line of code.

# count of negative values in the array ar
print(len(ar[ar < 0]))

Output:

2

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 negative values in a Numpy array. Note that in this method we’re not counting unique elements that are negative, rather we’re counting all values in an array that are negative (which may include duplicates depending on the array).

You might also be interested in –

• Numpy – Make All Negative Values Positive
• Numpy Array – Get All Values Greater than a Given Value
• Get unique values and counts in a numpy array
• Numpy – Make All Negative Values Zero in Array