Why does the `value_counts` function ignore a specific value?

Question

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a = [21,34,56,57,24,14,47,68]   

bins = np.arange(14, 68 + 5.4, 5.4)

pd.value_counts(pd.cut(a, bins, include_lowest=True),sort=False)

The number 68 is ignored by the value_counts function. You can see that the number of occurrences of the number in the interval (62.6, 68) is 0.

The number 68 is ignored by the value_counts function. You can see that the number of occurrences of the number in the interval (62.6, 68) is 0 — Elvin
– Elvin, Commented Nov 1, 2020 at 10:37

Uvar · Accepted Answer · 2020-11-04 15:19:31Z

1

Classic floating point arithmetic.

b = 14 + 10*5.4

c = 14+5.4+5.4+5.4+5.4+5.4+5.4+5.4+5.4+5.4+5.4 #10 increments

b==c
Out[195]: False

b-c
Out[196]: 1.4210854715202004e-14

b.as_integer_ratio()
Out[206]: (68, 1)

c.as_integer_ratio()
Out[207]: (4785074604081151, 70368744177664)

As your interval also starts just shy of 14, the exact integer ratio representation might be different, but the issue will still originate from the fact that the end of the final interval is up to floating point precision smaller than 68, thus not including 68 in its bin.

answered Nov 4, 2020 at 15:19

Uvar

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