Python for Finance

Chapter 2
----------
a : array_like
Calculate the standard deviation of these values.
axis : None or int or tuple of ints, optional
Axis or axes along which the standard deviation is computed. The
default is to compute the standard deviation of the flattened array.
.. versionadded: 1.7.0
Introduction to SciPy
The following are a few examples based on the functions enclosed in the SciPy
module. The sp.npv() function estimates the present values for a given set of cash
flows with the first cash flow happening at time zero. The first input value is the
discount rate, and the second input is an array of all cash flows.
The following is one example. Note that the sp.npv() function is different from the
Excel npv() function. We will explain why this is so in Chapter 3, Time Value of Money:
>>>import scipy as sp
>>>cashflows=[-100,50,40,20,10,50]
>>>x=sp.npv(0.1,cashflows)
>>>round(x,2)
>>>31.41
The sp.pmt() function is used to answer the following question.
What is the monthly cash flow to pay off a mortgage of $250,000 over 30 years
with an annual percentage rate (APR) of 4.5 percent, compounded monthly? The
following code shows the answer:
>>>payment=sp.pmt(0.045/12,30*12,250000)
>>>round(payment,2)
-1266.71
Based on the preceding result, the monthly payment will be $1,266.71. It might be
quite strange that we have a negative value. Actually, this sp.pmt() function mimics
the equivalent function in Excel, as we will see in the following screenshot:
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