Why are numpy functions so slow on pandas series / dataframes?

Question

Consider a small MWE, taken from another question:

DateTime                Data
2017-11-21 18:54:31     1
2017-11-22 02:26:48     2
2017-11-22 10:19:44     3         


        

Answer 1

Just read the source code, it's clear.

def clip(a, a_min, a_max, out=None):
    """a : array_like Array containing elements to clip."""
    return _wrapfunc(a, 'clip', a_min, a_max, out=out)

def _wrapfunc(obj, method, *args, **kwds):
    try:
        return getattr(obj, method)(*args, **kwds)
    #This situation has occurred in the case of
    # a downstream library like 'pandas'.
    except (AttributeError, TypeError):
        return _wrapit(obj, method, *args, **kwds)

def _wrapit(obj, method, *args, **kwds):
    try:
        wrap = obj.__array_wrap__
    except AttributeError:
        wrap = None
    result = getattr(asarray(obj), method)(*args, **kwds)
    if wrap:
        if not isinstance(result, mu.ndarray):
            result = asarray(result)
        result = wrap(result)
    return result

rectify：

after pandas v0.13.0_ahl1,pandas has it's own implement of clip.