Python Basics

1. Variables and data types

Scalar types and string type

Define a variable named a and assign to it the value 1.

a = 1

To print the value of the varaible a, we can either run print(a) or simplying type a.

print(a)

1

a

1

In Python, every variable has a type associated to it. To get the type of the varaible a, use type(a).

type(a)

int

Let’s define more variables and get their types.

## you can put multiple lines of codes inside a Jupyter notebook cell
b = 2.0
c = True
d = "Hello World!"

type(b), type(c), type(d)

(float, bool, str)

Collection types

Data types that can hold multiple values are called collection data types. In Python, there are four collection data types:

• List is a collection which is ordered and changeable. Allows duplicate members.

• Tuple is a collection which is ordered and unchangeable. Allows duplicate members.

• Set is a collection which is unordered and unindexed. No duplicate members.

• Dictionary is a collection which is unordered, changeable and indexed. No duplicate members.

List

L = [a, b, c]

type(L)

list

Python lists come with many built-in methods that allow you to access and manipulate the elements of the list and the list itself. You can find what methods are available for a list by running dir(list).

dir(list) ## or dir(L)

['__add__',
 '__class__',
 '__class_getitem__',
 '__contains__',
 '__delattr__',
 '__delitem__',
 '__dir__',
 '__doc__',
 '__eq__',
 '__format__',
 '__ge__',
 '__getattribute__',
 '__getitem__',
 '__getstate__',
 '__gt__',
 '__hash__',
 '__iadd__',
 '__imul__',
 '__init__',
 '__init_subclass__',
 '__iter__',
 '__le__',
 '__len__',
 '__lt__',
 '__mul__',
 '__ne__',
 '__new__',
 '__reduce__',
 '__reduce_ex__',
 '__repr__',
 '__reversed__',
 '__rmul__',
 '__setattr__',
 '__setitem__',
 '__sizeof__',
 '__str__',
 '__subclasshook__',
 'append',
 'clear',
 'copy',
 'count',
 'extend',
 'index',
 'insert',
 'pop',
 'remove',
 'reverse',
 'sort']

## to get help on a function, use the help function
help(list.append) ## or help(L.append)

Help on method_descriptor:

append(self, object, /) unbound builtins.list method
    Append object to the end of the list.

## access elements of a list using 0-based index
L[0], L[1], L[2]

(1, 2.0, True)

## access elements of a list using negative index
L[-1], L[-2], L[-3]

(True, 2.0, 1)

## access elements of a list using slicing
L[0:2], L[1:], L[:2]

([1, 2.0], [2.0, True], [1, 2.0])

## get the length of a list
len(L)

3

## append an element to a list
L.append(4)
print(L)

[1, 2.0, True, 4]

## insert an element to a list
L.insert(1, 3)
print(L)

[1, 3, 2.0, True, 4]

## remove an element from a list
L.remove(3)
print(L)

[1, 2.0, True, 4]

## pop an element from a list
L.pop()
print(L)

[1, 2.0, True]

## concatenate two lists
L2 = [5, 6]
L3 = L + L2
print(L3)

[1, 2.0, True, 5, 6]

Tuple

Tuple is similar to list, but it is immutable (i.e., you cannot change its elements once it is created).

t = (1, 2, 3)
print(type(t))

<class 'tuple'>

try:
    t.append(4)
except Exception as e:
    print(f"Error encountered: {e}")

Error encountered: 'tuple' object has no attribute 'append'

Set

s = {1, 2, 3}
print(s)
print(type(s))
print(len(s))

{1, 2, 3}
<class 'set'>
3

s.add(4) ## add an element to a set
print(s)
s.remove(4) ## remove an element from a set
print(s)

{1, 2, 3, 4}
{1, 2, 3}

## set operations
s1 = {1, 2, 3}
s2 = {3, 4, 5}
print(s1.union(s2))
print(s1.intersection(s2))
print(s1.difference(s2))

{1, 2, 3, 4, 5}
{3}
{1, 2}

Dictionaries

Dictionary is a collection of key-value pairs. Each key-value pair maps the key to its corresponding value. Dictionaries are unordered, so the order that the keys are added doesn’t necessarily reflect what order they may be reported back.

d = {"a": 1, "b": 2, "c": 3}
print(d)
print(type(d))
print(len(d))

{'a': 1, 'b': 2, 'c': 3}
<class 'dict'>
3

## access elements of a dictionary
print(d["a"])
print(d.get("a"))

## add an element to a dictionary
d["d"] = 4
print(d)

## remove an element from a dictionary
d.pop("d")
print(d)

## get the keys of a dictionary
print(d.keys())

## get the values of a dictionary
print(d.values())

## get the items of a dictionary
print(d.items())

1
1
{'a': 1, 'b': 2, 'c': 3, 'd': 4}
{'a': 1, 'b': 2, 'c': 3}
dict_keys(['a', 'b', 'c'])
dict_values([1, 2, 3])
dict_items([('a', 1), ('b', 2), ('c', 3)])

2. Control flow

Conditional statements

condition = True
if condition:
    print("Condition is True")
else:
    print("Condition is False")

Condition is True

a = 1
b = 2
if a > b:
    print("a is greater than b")
elif a < b:
    print("a is less than b")
else:
    print("a is equal to b")

a is less than b

Loops

## for loop
L = [0, 1, 2, 3, 4]
for i in L:
    print(i)

0
1
2
3
4

L = [0, 'hello world', 2.0, True, [1, 2, 3]]
for i in L:
    print(i)

0
hello world
2.0
True
[1, 2, 3]

## while loop
i = 0
while i < 5:
    print(i)
    i += 1

0
1
2
3
4

3. Functions

Functions are reusable pieces of code that accept inputs and produce outputs. They allow you reuse code and make your code more modular.

def sum_of_squares(a, b):
    return a**2 + b**2

print(sum_of_squares(3, 4))

25

def sum(L):
    s = 0
    for i in L:
        s += i
    return s

print(sum([1, 2, 3, 4, 5]))

15

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

print(mean([1, 2, 3, 4, 5]))

3.0

4. Classes and objects

Classes are a way to bundle data and functionality together. An object is an instance of a class. The data types we have been using so far are actually classes. For example, List is a class and list() or [] creates an object of the class List. Even the scalar types like int, float, str are classes in Python. When you create a variable of type str, you are creating an object of the class str. Remember that in Python, everything is an object of some class.

Besides the built-in classes, you can define your own classes. A class is defined using the class keyword followed by the class name. The class definition contains the attributes and methods of the class.

class Rectangle:
    def __init__(self, width, height):
        self.width = width
        self.height = height

    def area(self):
        return self.width * self.height

    def perimeter(self):
        return 2 * (self.width + self.height)

    def __str__(self):
        return f"Rectangle(width={self.width}, height={self.height})"

rec = Rectangle(3, 4)
print(rec.width)
print(rec.height)
print(rec.area())
print(rec.perimeter())
print(rec)

3
4
12
14
Rectangle(width=3, height=4)

5. Modules and packages

Python modules are files that contain Python code. A Python package is a directory that contains a collection of Python modules. You can import a module or a package using the import keyword.

import numpy as np

v = np.array([1, 2, 3])
print(v)
print(type(v))
print(v.shape)
print(v.sum())

[1 2 3]
<class 'numpy.ndarray'>
(3,)
6