pandas binning a list based on qcut of another list

Question

say I have a list:

a = [3, 5, 1, 1, 3, 2, 4, 1, 6, 4, 8]

and a sub list of a:

b = [5, 2, 6, 8]

I'd like to obtain bins by pd.qcut(a,2) and count number of values in each bin for list b. That is

In[84]: pd.qcut(a,2)
Out[84]: 
Categorical: 
[[1, 3], (3, 8], [1, 3], [1, 3], [1, 3], [1, 3], (3, 8], [1, 3], (3, 8], (3, 8], (3, 8]]
Levels (2): Index(['[1, 3]', '(3, 8]'], dtype=object)

Now I know the bins are: [1,3] and (3,8], and I'd like to know how many values in each bin for list "b". I can do this by hand when the number of bins is small, but what's the best approach when the number of bins is large?

Answer 1

You can use retbins paramether to get bins back from qcut:

>>> q, bins = pd.qcut(a, 2, retbins=True)

Then use pd.cut to get b indices with respect to bins:

>>> b = np.array(b)
>>> hist = pd.cut(b, bins, right=True).labels
>>> hist[b==bins[0]] = 0
>>> hist
array([1, 0, 1, 1])

Note that you have to treat corner case, bins[0], separately, as it is not included by cut in leftmost bin.