Check if a pandas Series has at least one item greater than a value

You could use any method to check if that condition is True at least for the one value:

In [36]: (s > 1).any()
Out[36]: True

in operator a.k.a __contains__() method checks if a specific value exists as an index in a Series.

s = pd.Series([0.5], index=['a'])

'a' in (s > 1)          # True
'b' in s                # False

As a side note, in operator used on dataframes checks if a value exists as a column label.

df = pd.DataFrame([[1]], columns=['a'])
'a' in df               # True
'b' in df               # False

In other words, the fact that the in operator returns True or False has nothing to do with whether (s > 1) has any True values in it or not. In order to make the membership test work, the values must be accessed.

True in (s < 1).values  # True

Reducing the values into a single boolean value (as suggested by @Anton Protopopov) is the canonical way to this task. Python's built-in any() function may be called as well.

any(s > 1)              # False
s.gt(1).any()           # False

(s < 1).any()           # True
s.lt(1).any()           # True