numpy.ipmt() in Python Last Updated : 29 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.ipmt(rate, nper, pv, fv, when = ‘end’) : This financial function helps user to compute payment value as per the interest only. i.e. returns the interest part. Parameters : rate : [scalar or (M, )array] Rate of interest as decimal (not per cent) per period nper : [scalar or (M, )array] total compounding periods fv : [scalar or (M, )array] Future value pv : [scalar or (M, )array] present value when : at the beginning (when = {‘begin’, 1}) or the end (when = {‘end’, 0}) of each period.Default is {‘end’, 0} Return : Payment value ie. the interest part of it. Equation being solved : fv + pv*(1+rate)**nper + pmt*(1 + rate*when)/rate*((1 + rate)**nper - 1) == 0 or when rate == 0 fv + pv + pmt * nper == 0 Code: Python3 1== # Python program explaining # ipmt() function import numpy as np ''' Question : monthly payment needed to pay off a $10, 000 loan in 12 years at an annual interest rate of 60 % ''' Solution = np.ipmt(0.6 / 12, 2 * 12, 1 * 12, 10000) # Here fv = 0 ; Also Default value of fv = 0 print("Solution - ipmt value : ", Solution) Output: Solution - ipmt value : 801.4432933339593 Comment More infoAdvertise with us Next Article numpy.ipmt() in Python mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Financial Functions Practice Tags : python Similar Reads Python | numpy.isnat() method With the help of numpy.isnat() method, we can get the boolean value as true if date defined in a np.datetime64() method is not a time by using numpy.isnat() method. Syntax : numpy.isnat() Return : Return the boolean value if time is not found. Example #1 : In this example we can see that by using nu 1 min read numpy.i0() function | Python numpy.i0() function is the modified Bessel function of the first kind, order 0. it's usually denoted by I0. Syntax : numpy.i0(x) Parameters : x : [array_like, dtype float or complex] Argument of the Bessel function. Return : [ndarray, shape = x.shape, dtype = x.dtype] The modified Bessel function ev 1 min read numpy.identity() in Python numpy.identity() function is used to create an identity matrix which is used to make identity matrix. This is commonly used in linear algebra and numerical computations. It has the following properties:Diagonal elements are all 1s.Non-diagonal elements are all 0s.Syntax: numpy.identity(n, dtype=None 1 min read Python NumPy Numpy is a general-purpose array-processing package. It provides a high-performance multidimensional array object, and tools for working with these arrays. It is the fundamental package for scientific computing with Python.Besides its obvious scientific uses, Numpy can also be used as an efficient m 6 min read NumPy Array in Python NumPy (Numerical Python) is a powerful library for numerical computations in Python. It is commonly referred to multidimensional container that holds the same data type. It is the core data structure of the NumPy library and is optimized for numerical and scientific computation in Python. Table of C 2 min read numpy.iinfo() function â Python numpy.iinfo() function shows machine limits for integer types. Syntax : numpy.iinfo(dtype) Parameters : dtype : [integer type, dtype, or instance] The kind of integer data type to get information about. Return : Machine limits for integer types. Code #1 : Python3 # Python program explaining # numpy. 1 min read numpy.info() function in Python In Numpy we can get all the information about the function, class, or module like what will the parameter and what will be the type of the return value with the help of numpy.info() function. This function returns the help information for a function, class, or module. Syntax: numpy.info(numpy.info(o 1 min read Python | numpy.lookfor() method With the help of numpy.lookfor() method, we can get the information about the module in the numpy by using numpy.lookfor() method. Syntax : numpy.lookfor(module_name) Return : Return the information about the module. Example #1 : In this example we can see that by using numpy.lookfor() method, we ar 1 min read numpy.who function - Python numpy.who() function print the NumPy arrays in the given dictionary. Syntax : numpy.who(vardict = None) Parameters : vardict : [dict, optional] A dictionary possibly containing ndarrays. Return : Returns âNoneâ. If there is no dictionary passed in or vardict is None then returns NumPy arrays in the 1 min read numpy.fromstring() function â Python numpy.fromstring() function create a new one-dimensional array initialized from text data in a string. Syntax : numpy.fromstring(string, dtype = float, count = -1, sep = ' ') Parameters : string : [str] A string that contained the data. dtype : [data-type, optional] Data-type of the array. Default d 1 min read Like