Functions

By Salerno | February 29, 2020

1. Defining functions


def square(number):
  print("The square of", number, "is", number ** 2)

square(7)
## The square of 7 is 49

2. Functions with multiple parameters


def maximum(value1, value2, value3):
  max_value = value1
  if value2 > max_value:
    max_value = value2
  if value3 > max_value:
    max_value = value3
  return max_value


maximum(12, 27, 36)
## 36
maximum('yellow', 'red', 'orange')
## 'yellow'

3. Random-Number Generation



import random

random.seed(10)

for roll in range(10):
  print(random.randrange(1,7), end=" ")
## 5 1 4 4 5 1 2 4 4 3

import random

for i in range(20):
  print("H" if random.randrange(2) == 0 else "T", end=" ")
## H H T T H H T H T H T T T T T T H T T H

4. Unpacking tuples


student = ("Sue", [89, 94, 85])

name, grades = student

print(f'{name}: {grades}')
## Sue: [89, 94, 85]

5. Math Module Functions


import math

math.ceil(9.2)
## 10
math.floor(9.2)
## 9
math.exp(9.2)
## 9897.129058743909
math.log(9.2)
## 2.2192034840549946
math.log10(9.2)
## 0.9637878273455552
math.pow(3, 2)
## 9.0
math.sqrt(49)
## 7.0
math.fabs(-10)
## 10.0
math.fmod(9.8, 4.0)
## 1.8000000000000007

6. Default Parameter Values


def rectangle_area(length=2, width=3):
  return length * width
  
rectangle_area()
## 6
rectangle_area(10)
## 30
rectangle_area(10, 5)
## 50

7. Arbitrary Argument Lists


def average(*args):
  return sum(args) / len(args)
  
average(5, 10)
## 7.5
average(5, 10, 15)
## 10.0
average(5, 10, 15, 20)
## 12.5
grades = [88, 75, 96, 55, 83]

average(*grades)
## 79.4

8. Methods: Functions that belong to objects


s = "Hello"

s.lower()
## 'hello'
s.upper()
## 'HELLO'
s

## 'Hello'

9. Scope rules


#acessing a global variable from a function

x = 7

def access_global():
  print('x printed from access_global:', x)

access_global()
## x printed from access_global: 7

# trying to modify a global variable

def try_to_modify_global():
  x = 3.5
  print('x printed from try_to_modify_global:', x)

try_to_modify_global()
## x printed from try_to_modify_global: 3.5
x
## 7

def modify_global():
  global x
  x = 'hello'
  print('x printed from modify_global:', x)

modify_global()
## x printed from modify_global: hello
x
## 'hello'

10. Import


from math import ceil, floor

ceil(10.7)
## 11
floor(10.7)
## 10
# wildcards

from math import *

e
## 2.718281828459045

11. Binding names for modules and module identifiers


import statistics as stats

grades = [85, 93, 45, 87, 93]

stats.mean(grades)
## 80.6

12. Object Identities


id(grades)
## 426617288

13. Data Science: Measures of Dispersion


import math, statistics

y = [-2.5, -0.5, -1.5, 2.5, 1.5, -0.5, 0.5, 1.5, -1.5]

statistics.pvariance(y)
## 2.4691358024691357
statistics.pstdev(y)
## 1.5713484026367723
math.sqrt(statistics.pvariance(y))
## 1.5713484026367723

14. Example


from sklearn import datasets
import pandas as pd

iris = datasets.load_iris()
data_iris = iris.data

digits = datasets.load_digits()
data_digits = digits.data

type(iris)
## <class 'sklearn.utils.Bunch'>
type(data_iris)
## <class 'numpy.ndarray'>
type(digits)
## <class 'sklearn.utils.Bunch'>
type(data_digits)

## <class 'numpy.ndarray'>

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