def derivative(self, n=<NUM_LIT:1>):
tck = fitpack.splder(self._eval_args, n)<EOL>return UnivariateSpline._from_tck(tck, self.ext)<EOL>
Construct a new spline representing the derivative of this spline.

Parameters
----------
n : int, optional
    Order of derivative to evaluate. Default: 1

Returns
-------
spline : UnivariateSpline
    Spline of order k2=k-n representing the derivative of this
    spline.

See Also
--------
splder, antiderivative

Notes
-----

.. versionadded:: 0.13.0

Examples
--------
This can be used for finding maxima of a curve:

>>> from scipy.interpolate import UnivariateSpline
>>> x = np.linspace(0, 10, 70)
>>> y = np.sin(x)
>>> spl = UnivariateSpline(x, y, k=4, s=0)

Now, differentiate the spline and find the zeros of the
derivative. (NB: `sproot` only works for order 3 splines, so we
fit an order 4 spline):

>>> spl.derivative().roots() / np.pi
array([ 0.50000001,  1.5       ,  2.49999998])

This agrees well with roots :math:`\pi/2 + n\pi` of `cos(x) = sin'(x)`.