ajschumacher

import random
import math

def mean(elements):
    return sum(elements) / len(elements)

def euclidean_dist(first, second):
    assert len(first) == len(second)
    return sum((f - s)**2 for f, s in zip(first, second))**0.5

ajschumacher

# inspired by and based on:
# https://julien.danjou.info/python-exceptions-guide/
# https://github.com/jd/julien.danjou.info/blob/master/bin/generate-python-exceptions-graph.py

import builtins

edges = set()
synonyms = {}
for name in dir(builtins):
    item = getattr(builtins, name)

ajschumacher

SQL workshop!

---

Get everything you can about people.

select * from people

-- comments

ajschumacher

chi-squared test

import scipy.stats

obs = np.array([[a, b],
                [c, d]])
_, p, _, _ = scipy.stats.chi2_contingency(obs)

ajschumacher

def linterp(x_1, y_1, x_2, y_2, x_new):
    """Linear interpolation"""
    assert min(x_1, x_2) <= x_new <= max(x_1, x_2), 'extrapolation'
    factor = (x_new - x_1) / (x_2 - x_1)
    y_new = factor * (y_2 - y_1) + y_1
    return y_new

assert linterp(0, 0, 2, 2, 1) == 1
assert linterp(-2, -1, 2, 0, -1) == -0.75
assert linterp(1.2, 1.2, 0.8, 0.8, 1) == 1