Plot bin sizes in Python

I've cut my data into several bins and would like to plot the size/frequency of each bin in a histogram. With the y-axis being the bin frequency and the x labels being the bin ranges.

Currently I have:

out = pd.cut(data.hour, bins = filter_values, include_lowest = True)
counts = pd.value_counts(out)
print(counts)`

Which outputs:

[0, 5]      1000
(19, 23]       0
(15, 19]       0
(11, 15]       0
(8, 11]        0
(5, 8]         0
Name: hour, dtype: int64

How would I go about this?

Solution

Demo (step by step):

In [51]: filter_values = [0, 5, 11, 15, 19, 23]

generating sample DF:

In [52]: df = pd.DataFrame({'hour':np.random.randint(0, 23, 20)})

In [53]: df
Out[53]:
    hour
0      5
1     18
2     19
3      5
4     16
5     18
6     18
7     19
8      0
9      8
10    14
11    20
12     9
13    22
14     8
15     0
16     0
17     4
18    13
19    18

building bins

In [54]: out = pd.cut(data.hour, bins = filter_values, include_lowest = True)

In [55]: out
Out[55]:
0       [0, 5]
1     (11, 15]
2     (15, 19]
3     (11, 15]
4      (5, 11]
5       [0, 5]
6       [0, 5]
7       [0, 5]
8       [0, 5]
9      (5, 11]
10      [0, 5]
11      [0, 5]
12    (11, 15]
13    (15, 19]
14     (5, 11]
15    (15, 19]
16     (5, 11]
17    (19, 23]
18     (5, 11]
19      [0, 5]
Name: hour, dtype: category
Categories (5, object): [[0, 5] < (5, 11] < (11, 15] < (15, 19] < (19, 23]]

counts:

In [56]: counts = out.value_counts(sort=False)

In [57]: counts
Out[57]:
[0, 5]      8
(5, 11]     5
(11, 15]    3
(15, 19]    3
(19, 23]    1
Name: hour, dtype: int64

plot

In [58]: counts.plot.bar(rot=False)
Out[58]: <matplotlib.axes._subplots.AxesSubplot at 0xa427b00>