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%matplotlib inline

Doing Math with Python

Amit Saha

May 30, PyCon US 2016

Portland, Oregon

About me

Software Engineer at Freelancer.com HQ in Sydney, Australia
Author of "Doing Math with Python" (No Starch Press, 2015)
Writes for Linux Voice, Linux Journal, and others.
Blog, GitHub

Contact

Book: Doing Math with Python

Use PYCONMATH code to get 30% off "Doing Math with Python" from No Starch Press

(Valid from May 26th - June 8th)

Book Signing - May 31st - 2.00 PM - No Starch Press booth

What?

Python can lead to a more enriching learning and teaching experience in the classroom

How? Next slides

Tools (or, Giant shoulders we will stand on)

Python 3, SymPy, matplotlib

*Individual logos are copyright of the respective projects. Source of the "giant shoulders" image.

Python - a scientific calculator

Whose calculator looks like this?

>>> (131 + 21.5 + 100.2 + 88.7 + 99.5 + 100.5 + 200.5)/4
185.475

Python 3 is my favorite calculator (not Python 2 because 1/2 = 0)

Beyond basic operations:

fabs(), abs(), sin(), cos(), gcd(), log() and more (See math)
Descriptive statistics (See statistics)

Python - a scientific calculator

Develop your own functions: unit conversion, finding correlation, .., anything really
Use PYTHONSTARTUP to extend the battery of readily available mathematical functions

$ PYTHONSTARTUP=~/work/dmwp/pycon-us-2016/startup_math.py idle3 -s

Unit conversion functions

>>> unit_conversion()
1. Kilometers to Miles
2. Miles to Kilometers
3. Kilograms to Pounds
4. Pounds to Kilograms
5. Celsius to Fahrenheit
6. Fahrenheit to Celsius
Which conversion would you like to do? 6
Enter temperature in fahrenheit: 98
Temperature in celsius: 36.66666666666667
>>>

Finding linear correlation

>>> 
>>> x = [1, 2, 3, 4]
>>> y = [2, 4, 6.1, 7.9]
>>> find_corr_x_y(x, y)
0.9995411791453812

Python - a really fancy calculator

SymPy - a pure Python symbolic math library

from sympy import awesomeness - don't try that :)



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# Create graphs from algebraic expressions

from sympy import Symbol, plot
x = Symbol('x')
p = plot(2*x**2 + 2*x + 2)



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# Solve equations

from sympy import solve, Symbol
x = Symbol('x')
solve(2*x + 1)









    Out[13]:





[-1/2]



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# Limits

from sympy import Symbol, Limit, sin
x = Symbol('x')
Limit(sin(x)/x, x, 0).doit()









    Out[24]:





1



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# Derivative

from sympy import Symbol, Derivative, sin, init_printing
x = Symbol('x')
init_printing()
Derivative(sin(x)**(2*x+1), x).doit()









    Out[2]:





$$\left(\frac{\left(2 x + 1\right) \cos{\left (x \right )}}{\sin{\left (x \right )}} + 2 \log{\left (\sin{\left (x \right )} \right )}\right) \sin^{2 x + 1}{\left (x \right )}$$



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# Indefinite integral

from sympy import Symbol, Integral, sqrt, sin, init_printing
x = Symbol('x')
init_printing()
Integral(sqrt(x)).doit()









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$$\frac{2 x^{\frac{3}{2}}}{3}$$



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# Definite integral

from sympy import Symbol, Integral, sqrt
x = Symbol('x')
Integral(sqrt(x), (x, 0, 2)).doit()









    Out[19]:





$$\frac{4 \sqrt{2}}{3}$$

Can we do more than write smart calculators?

Python - Making other subjects more lively

matplotlib
basemap
Interactive Jupyter Notebooks

Bringing Science to life

Animation of a Projectile motion (Python Source)



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from IPython.display import YouTubeVideo
YouTubeVideo("8uWRVh58KdQ")









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Exploring Fractals in Nature

Interactively drawing a Barnsley Fern (Notebook)

The world is your graph paper

Showing places on a digital map (Notebook)

Great base for the future

Statistics and Graphing data -> Data Science

Differential Calculus -> Machine learning