How to Count Occurrences of Elements in NumPy Arrays?

Counting Occurrences in NumPy Array

NumPy arrays are used extensively for numerical computations, and a common task is to count the occurrence of specific elements within them. However, unlike lists and other Python data structures, NumPy arrays do not have a built-in count method.

Using NumPy's unique

The numpy.unique function can be employed to determine the unique values in an array and their respective counts. It takes an optional parameter return_counts, which when set to True, returns both the unique values and their corresponding counts. For instance:

<code class="python">import numpy

# Create a NumPy array
y = np.array([0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1])

# Obtain unique values and their counts
unique, counts = numpy.unique(y, return_counts=True)

# Convert the results to a dictionary for ease of access
results = dict(zip(unique, counts))

print(results)  # Output: {0: 7, 1: 4}</code>

Non-NumPy Method: Using collections.Counter

Alternatively, you can use the collections.Counter class from outside NumPy. This class is specifically designed for counting occurrences in any iterable, including NumPy arrays:

<code class="python">import collections

# Use the Counter class to tally the occurrences of each element
counter = collections.Counter(y)

# Print the Counter object to view the occurrences
print(counter)  # Output: Counter({0: 7, 1: 4})</code>

The above is the detailed content of How to Count Occurrences of Elements in NumPy Arrays?. For more information, please follow other related articles on the PHP Chinese website!