python - Pandas groupby how to compute counts in ranges

Question

Say I have a huge list of numbers between 0 and 100. I compute ranges, depending on the max number and then saying there are 10 bins. So my ranges are for example

ranges = [0,10,20,30,40,50,60,70,80,90,100]

Now I count the occurances in each range from 0-10, 10-20, and so on. I iterate over every number in the list and check for a range. I assume this is not the best way in terms of runtime speed.

Can I fasten it up by using pandas, e.g. pandas.groupby, and how?

Answer 1

We can use pd.cut to bin the values into ranges, then we can groupby these ranges, and finally call count to count the values now binned into these ranges:

np.random.seed(0)
df = pd.DataFrame({"a": np.random.random_integers(1, high=100, size=100)})
ranges = [0,10,20,30,40,50,60,70,80,90,100]
df.groupby(pd.cut(df.a, ranges)).count()

            a
a            
(0, 10]    11
(10, 20]   10
(20, 30]    8
(30, 40]   13
(40, 50]   11
(50, 60]    9
(60, 70]   10
(70, 80]   11
(80, 90]   13
(90, 100]   4