numpy.real(val) [source] Return the real part of the elements of the array. Parameters: val : array_like Input array. Returns: out : ndarray Output array. If val is real, the type of val is used for the output. If val has complex elements, the returned type is float. See also real_if_close, imag, angle Examples >>> a = np.array([1+2j, 3+4j, 5+6j]) >>> a.real array([ 1., 3., 5.]) >>> a.real = 9 >>> a array([ 9.+2.j, 9.+4.j, 9.+6.j]) >>&

chararray.replace(old, new, count=None) [source] For each element in self, return a copy of the string with all occurrences of substring old replaced by new. See also char.replace

numpy.all(a, axis=None, out=None, keepdims=False) [source] Test whether all array elements along a given axis evaluate to True. Parameters: a : array_like Input array or object that can be converted to an array. axis : None or int or tuple of ints, optional Axis or axes along which a logical AND reduction is performed. The default (axis = None) is to perform a logical AND over all the dimensions of the input array. axis may be negative, in which case it counts from the last to the first

generic.conj()

numpy.roots(p) [source] Return the roots of a polynomial with coefficients given in p. The values in the rank-1 array p are coefficients of a polynomial. If the length of p is n+1 then the polynomial is described by: p[0] * x**n + p[1] * x**(n-1) + ... + p[n-1]*x + p[n] Parameters: p : array_like Rank-1 array of polynomial coefficients. Returns: out : ndarray An array containing the complex roots of the polynomial. Raises: ValueError When p cannot be converted to a rank-1 array.

chararray.isnumeric() [source] For each element in self, return True if there are only numeric characters in the element. See also char.isnumeric

numpy.polynomial.polynomial.polyval2d(x, y, c) [source] Evaluate a 2-D polynomial at points (x, y). This function returns the value The parameters x and y are converted to arrays only if they are tuples or a lists, otherwise they are treated as a scalars and they must have the same shape after conversion. In either case, either x and y or their elements must support multiplication and addition both with themselves and with the elements of c. If c has fewer than two dimensions, ones are i

numpy.mirr(values, finance_rate, reinvest_rate) [source] Modified internal rate of return. Parameters: values : array_like Cash flows (must contain at least one positive and one negative value) or nan is returned. The first value is considered a sunk cost at time zero. finance_rate : scalar Interest rate paid on the cash flows reinvest_rate : scalar Interest rate received on the cash flows upon reinvestment Returns: out : float Modified internal rate of return

dtype.itemsize The element size of this data-type object. For 18 of the 21 types this number is fixed by the data-type. For the flexible data-types, this number can be anything.

matrix.itemsize Length of one array element in bytes. Examples >>> x = np.array([1,2,3], dtype=np.float64) >>> x.itemsize 8 >>> x = np.array([1,2,3], dtype=np.complex128) >>> x.itemsize 16