Functions

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'>