Counting number of specific numbers in the column of a numpy array in python

Question

I have a question, which is probably very simple to solve but I just couldn't find an answer. I want to count the number of the values 0, 1 and 2 in the column of a numpy array. My array has two columns, and I want to count the values 0, 1 and 2 in the second column. I tried to solve this like this:

   for row in vergleich[:,1]:
       n = vergleich[:,1].count(0)
       o = vergleich[:,1].count(1)
       t = vergleich[:,1].count(2)
       print(n)
       print(o)
       print(t)

But I get the error message : AttributeError: 'numpy.ndarray' object has no attribute 'count' What are other ways to solve this? Thanks in advance :)

you can use np.count_nonzero(<condition on array>) to count. example: np.count_nonzero(a==0) — N.Moudgil
– N.Moudgil, Commented Jan 31, 2020 at 9:33
Does this answer your question? How to count the occurrence of certain item in an ndarray in Python? — offeltoffel
– offeltoffel, Commented Jan 31, 2020 at 9:41
Check out the link stackoverflow.com/questions/28663856/… Hope this helps! — Swati Srivastava
– Swati Srivastava, Commented Jan 31, 2020 at 9:58

Valdi_Bo · Accepted Answer · 2020-01-31 11:18:54Z

1

Run: np.count_nonzero(vergleich[:,1] == 0), the same for other numbers of interest.

Another, more general alternative:

unique, counts = np.unique(vergleich[:,1], return_counts=True)
result = dict(zip(unique, counts))

Then result will contain key / value pairs:

key - value in your column,
value - how many times it occurred.

So then you may query result for keys 0, 1 and 2.

Yet another option, but this time based on Pandas:

Run: res = pd.value_counts(vergleich[:,1])

The result is a Pandas Series with:

index - a value in the source Series (a Numpy 1-D array can also be passed),
value - how many times it occurred.

edited Jan 31, 2020 at 11:18

answered Jan 31, 2020 at 11:05

Valdi_Bo

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