docstr: Evaluate a single derivative of the polynomial at the point `x`.
  
  Parameters
  ----------
  x : array_like
      Point or points at which to evaluate the derivatives
  
  der : integer, optional
      Which derivative to evaluate (default: first derivative).
      This number includes the function value as 0th derivative.
  
  Returns
  -------
  d : ndarray
      Derivative interpolated at the x-points. Shape of `d` is
      determined by replacing the interpolation axis in the
      original array with the shape of `x`.
  
  Notes
  -----
  This may be computed by evaluating all derivatives up to the desired
  one (using self.derivatives()) and then discarding the rest.
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code: def derivative(self, x, der=1):
      """
      Evaluate a single derivative of the polynomial at the point `x`.
  
      Parameters
      ----------
      x : array_like
          Point or points at which to evaluate the derivatives
  
      der : integer, optional
          Which derivative to evaluate (default: first derivative).
          This number includes the function value as 0th derivative.
  
      Returns
      -------
      d : ndarray
          Derivative interpolated at the x-points. Shape of `d` is
          determined by replacing the interpolation axis in the
          original array with the shape of `x`.
  
      Notes
      -----
      This may be computed by evaluating all derivatives up to the desired
      one (using self.derivatives()) and then discarding the rest.
  
      """
      x, x_shape = self._prepare_x(x)
      y = self._evaluate_derivatives(x, der + 1)
      return self._finish_y(y[der], x_shape)
  
imports: import warnings
  import numpy
  from scipy.special import factorial
  from scipy._lib._util import _asarray_validated, float_factorial, check_random_state
label_desc: Use image node_id 2 for calling the _Interpolator1DWithDerivatives obj's underlying member method code with example usage: obj.derivative(x, der) and returns: self