numpy.cov(m, y=None, rowvar=True, bias=False, ddof=None, fweights=None, aweights=None) [source] Estimate a covariance matrix, given data and weights. Covariance indicates the level to which two variables vary together. If we examine N-dimensional samples, , then the covariance matrix element is the covariance of and . The element is the variance of . See the notes for an outline of the algorithm. Parameters: m : array_like A 1-D or 2-D array containing multiple variables and observatio

chararray.startswith(prefix, start=0, end=None) [source] Returns a boolean array which is True where the string element in self starts with prefix, otherwise False. See also char.startswith

MaskedArray.__long__() <==> long(x)

numpy.take(a, indices, axis=None, out=None, mode='raise') [source] Take elements from an array along an axis. This function does the same thing as ?fancy? indexing (indexing arrays using arrays); however, it can be easier to use if you need elements along a given axis. Parameters: a : array_like The source array. indices : array_like The indices of the values to extract. New in version 1.8.0. Also allow scalars for indices. axis : int, optional The axis over which to select values.

numpy.restoredot() [source] Restore dot, vdot, and innerproduct to the default non-BLAS implementations. Typically, the user will only need to call this when troubleshooting and installation problem, reproducing the conditions of a build without an accelerated BLAS, or when being very careful about benchmarking linear algebra operations. Note Deprecated in Numpy 1.10 The cblas functions have been integrated into the multarray module and restoredot now longer does anything. It will be remov

numpy.median(a, axis=None, out=None, overwrite_input=False, keepdims=False) [source] Compute the median along the specified axis. Returns the median of the array elements. Parameters: a : array_like Input array or object that can be converted to an array. axis : {int, sequence of int, None}, optional Axis or axes along which the medians are computed. The default is to compute the median along a flattened version of the array. A sequence of axes is supported since version 1.9.0. out : n

nditer.copy() Get a copy of the iterator in its current state. Examples >>> x = np.arange(10) >>> y = x + 1 >>> it = np.nditer([x, y]) >>> it.next() (array(0), array(1)) >>> it2 = it.copy() >>> it2.next() (array(1), array(2))

numpy.load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII') [source] Load arrays or pickled objects from .npy, .npz or pickled files. Parameters: file : file-like object or string The file to read. File-like objects must support the seek() and read() methods. Pickled files require that the file-like object support the readline() method as well. mmap_mode : {None, ?r+?, ?r?, ?w+?, ?c?}, optional If not None, then memory-map the file, using the given mode (see

Polynomial.copy() [source] Return a copy. Returns: new_series : series Copy of self.

record.max() Not implemented (virtual attribute) Class generic exists solely to derive numpy scalars from, and possesses, albeit unimplemented, all the attributes of the ndarray class so as to provide a uniform API. See also The