Finding matching interval(s) in pandas Intervalindex

There's this interesting API called Intervalindex new in 0.20 that lets you create an index of intervals.

Given some sample data:

data = [(893.1516130000001, 903.9187099999999),
 (882.384516, 893.1516130000001),
 (817.781935, 828.549032)]

You can create the index like this:

idx = pd.IntervalIndex.from_tuples(data)

print(idx)
IntervalIndex([(893.151613, 903.91871], (882.384516, 893.151613], (817.781935, 828.549032]]
              closed='right',
              dtype='interval[float64]')

An interesting property of Intervals is that you can perform interval checks with in:

print(y[-1])
Interval(817.78193499999998, 828.54903200000001, closed='right')

print(820 in y[-1])
True

print(1000 in y[-1])
False

I would like to know how to apply this operation to the entire index. For example, given some number 900, how could I retrieve a boolean mask of intervals for which this number fits in?

I can think of:

m = [900 in y for y in idx]
print(m)
[True, False, False]

Are there better ways to do this?

from Finding matching interval(s) in pandas Intervalindex