Counting Occurrences in Numpy Arrays
In order to determine the frequency of specific elements within a Numpy array, various approaches exist. One common method involves utilizing the numpy.unique function. This function identifies the distinct elements in the array and returns a corresponding array of counts for each unique value.
Consider the following example array:
y = np.array([0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1])
Using numpy.unique:
<code class="python">import numpy unique, counts = numpy.unique(y, return_counts=True) print(dict(zip(unique, counts)))</code>
This will output a dictionary with the unique elements (0 and 1) as keys and their corresponding counts as values.
Alternatively, a non-NumPy method using collections.Counter can be employed:
<code class="python">import collections, numpy y = np.array([0, 0, 0, 1, 0, 1, 1, 0, 0, 0, 0, 1]) counter = collections.Counter(y) print(counter)</code>
This will provide a Counter object with the unique elements as keys and their counts as values.
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