﻿ Py Sci - Introducing Python (2014) ﻿

## Introducing Python (2014)

### Appendix C. Py Sci

In her reign the power of steam
On land and sea became supreme,
And all now have strong reliance
In fresh victories of science.

— James McIntyre Queen’s Jubilee Ode 1887

In the past few years, largely because of the software you’ll see in this appendix, Python has become extremely popular with scientists. If you’re a scientist or student yourself, you might have used tools like MATLAB and R, or traditional languages such as Java, C, or C++. In this appendix, you’ll see how Python makes an excellent platform for scientific analysis and publishing.

Math and Statistics in the Standard Library

First, let’s take a little trip back to the standard library and visit some features and modules that we’ve ignored.

Math Functions

Python has a menagerie of math functions in the standard math library. Just type import math to access them from your programs.

It has a few constants such as pi and e:

>>> import math

>>> math.pi

>>> 3.141592653589793

>>> math.e

2.718281828459045

Most of it consists of functions, so let’s look at the most useful ones.

fabs() returns the absolute value of its argument:

>>> math.fabs(98.6)

98.6

>>> math.fabs(-271.1)

271.1

Get the integer below (floor()) and above (ceil()) some number:

>>> math.floor(98.6)

98

>>> math.floor(-271.1)

-272

>>> math.ceil(98.6)

99

>>> math.ceil(-271.1)

-271

Calculate the factorial (in math, n !) by using

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