r is a numpy (rec)array. So
r["dt"] >= startdate is also a (boolean) array. For numpy arrays the
& operation returns the elementwise-and of the two boolean arrays.
The NumPy developers felt there was no one commonly understood way to evaluate an array in boolean context: it could mean
True if any element is
True, or it could mean
True if all elements are
True if the array has non-zero length, just to name three possibilities.
Since different users might have different needs and different assumptions, the NumPy developers refused to guess and instead decided to raise a ValueError whenever one tries to evaluate an array in boolean context. Applying
and to two numpy arrays causes the two arrays to be evaluated in boolean context (by calling
__bool__ in Python3 or
__nonzero__ in Python2).
Your original code
mask = ((r["dt"] >= startdate) & (r["dt"] <= enddate)) selected = r[mask]
looks correct. However, if you do want
and, then instead of
a and b use