My first lab

Kirstie Whitaker

June 15th 2017

Cape Town, SA

About me

  • 2016/17 Mozilla Fellow for Science

  • Research Fellow at the Alan Turing Institute for Data Science, London

  • Research Associate in the Department of Psychiatry at the University of Cambridge

Contact

Slides: https://doingmathwithpython.github.io/pycon-us-2016/

All presentation materials: https://github.com/doingmathwithpython

This talk - a proposal, a hypothesis, a statement

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 :)

In [5]:
# Create graphs from algebraic expressions

from sympy import Symbol, plot
x = Symbol('x')
p = plot(2*x**2 + 2*x + 2)
In [13]:
# Solve equations

from sympy import solve, Symbol
x = Symbol('x')
solve(2*x + 1)
Out[13]:
[-1/2]
In [24]:
# Limits

from sympy import Symbol, Limit, sin
x = Symbol('x')
Limit(sin(x)/x, x, 0).doit()
Out[24]:
1
In [2]:
# Derivative

from sympy import Symbol, Derivative, sin, init_printing
x = Symbol('x')
init_printing()
Derivative(sin(x)**(2*x+1), x).doit()
Out[2]:
$$\left(\frac{\left(2 x + 1\right) \cos{\left (x \right )}}{\sin{\left (x \right )}} + 2 \log{\left (\sin{\left (x \right )} \right )}\right) \sin^{2 x + 1}{\left (x \right )}$$
In [16]:
# Indefinite integral

from sympy import Symbol, Integral, sqrt, sin, init_printing
x = Symbol('x')
init_printing()
Integral(sqrt(x)).doit()
Out[16]:
$$\frac{2 x^{\frac{3}{2}}}{3}$$
In [19]:
# 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)

In [3]:
from IPython.display import YouTubeVideo
YouTubeVideo("8uWRVh58KdQ")
Out[3]:

Exploring Fractals in Nature

Interactively drawing a Barnsley Fern (Notebook)

</img>

The world is your graph paper

Showing places on a digital map (Notebook)

Book: Doing Math With Python

Overview

  • All of what I have discussed so far

  • In addition: Descriptive statistics, Sets and Probability, Random numbers

Published by No Starch Press in August, 2015.

Upcoming/In-progress translations: Simplified Chinese, Japanese, French and Korean.

Comments

Saha does an excellent job providing a clear link between Python and upper-level math concepts, and demonstrates how Python can be transformed into a mathematical stage. This book deserves a spot on every geometry teacher’s bookshelf.

School Library Journal

Outstanding guide to using Python to do maths. Working back through my undergrad maths using Python.

Saha does an excellent job providing a clear link between Python and upper-level math concepts, and demonstrates how Python can be transformed into a mathematical stage.

This book is highly recommended for the high school or college student and anyone who is looking for a more natural way of programming math and scientific functions

As a teacher I highly recommend this book as a way to work with someone in learning both math and programming

Great base for the future

Statistics and Graphing data -> Data Science

Differential Calculus -> Machine learning

Application of differentiation

Use gradient descent to find a function's minimum value (Notebook)

Predict the college admission score based on high school math score

Use gradient descent as the optimizer for single variable linear regression model (Notebook)

Dialogue

Questions, Thoughts, comments, discussions?

Online

  • Twitter: @echorand

  • Email: amitsaha.in@gmail.com

PyCon Special!

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

Acknowledgements

PyCon US Education Summit team for inviting me

Thanks to PyCon US for reduced registration rates

Massive thanks to my employer, Freelancer.com for sponsoring my travel and stay