All posts by Datasciencelovers

Python String Formatting

String formatting lets you inject items into a string rather than trying to chain items together using commas or string concatenation. As a quick comparison, consider:

player = ‘Thomas’
points = 33
‘Last night, ‘+player+’ scored ‘+str(points)+’ points.’ # concatenation
f’Last night, {player} scored {points} points.’ # string formatting

There are three ways to perform string formatting.

  • The oldest method involves placeholders using the modulo % character.
  • An improved technique uses the .format() string method.
  • The newest method, introduced with Python 3.6, uses formatted string literals, called f-strings.

Since you will likely encounter all three versions in someone else’s code, we describe each of them here.

Let’s explore the concept through jupyter notebook.

Python List

List is a collection which is ordered and changeable. It allows duplicate members.

A list can be defined as a collection of values or items of different types. The items in the list are separated with the comma (,) and enclosed with the square brackets [].

A list can be defined as follows.

L1 = [“John”, 102, “USA”]
L2 = [1, 2, 3, 4, 5, 6]
L3 = [1, “Ryan”]

Let’s explore more concepts about list through following jupyter notebook exercise.

Python Dictionaries

A dictionary is a collection which is unordered, changeable and indexed. In Python dictionaries are written with curly brackets, and they have keys and values.

dict = {‘Name’: ‘Zara’, ‘Age’: 7, ‘Class’: ‘First’}
print “dict[‘Name’]: “, dict[‘Name’]
print “dict[‘Age’]: “, dict[‘Age’]

When the above code is executed, it produces the following result

dict[‘Name’]: Zara
dict[‘Age’]: 7

Let’s Explore more about dictionaries through jupyter notebook.

Python Sets

A set is a collection which is unordered and unindexed. In Python sets are written with curly brackets.


thisset = {“apple”, “banana”, “cherry”}

Access Items

You cannot access items in a set by referring to an index, since sets are unordered the items has no index.

But you can loop through the set items using a for loop, or ask if a specified value is present in a set, by using the in keyword.

Let’s explore Sets and Booleans concepts with Jupyter notebook.

Comparison Operators

In this lecture we will be learning about Comparison Operators in Python. These operators will allow us to compare variables and output a Boolean value (True or False).

If you have any sort of background in Math, these operators should be very straight forward.

First we’ll present a table of the comparison operators and then work through some examples:

Table of Comparison Operators 

In the table below, a=3 and b=4.

==If the values of two operands are equal, then the condition becomes true.(a == b) is not true.
!=If values of two operands are not equal, then condition becomes true.(a != b) is true
>If the value of left operand is greater than the value of right operand, then condition becomes true.(a > b) is not true.
<If the value of left operand is less than the value of right operand, then condition becomes true.(a < b) is true.
>=If the value of left operand is greater than or equal to the value of right operand, then condition becomes true.(a >= b) is not true.
<=If the value of left operand is less than or equal to the value of right operand, then condition becomes true.(a <= b) is true.

Let’s now work in jupyter notebook through quick examples of each of these.

Python Statements

In this post we will be doing a quick overview of Python Statements. This post will emphasize differences between Python and other languages such as C++.

There are two reasons we take this approach for learning the context of Python Statements:

  • If you are coming from a different language this will rapidly accelerate your understanding of Python.
  • Learning about statements will allow you to be able to read other languages more easily in the future.

Python vs Other Languages

Let’s create a simple statement that says: “If a is greater than b, assign 2 to a and 4 to b”

Take a look at these two if statements (we will learn about building out if statements soon).

Version 1 (Other Languages)

if (a>b){
a = 2;
b = 4;

Version 2 (Python)

if a>b:
a = 2
b = 4

You’ll notice that Python is less cluttered and much more readable than the first version. How does Python manage this?

Let’s walk through the main differences:

Python gets rid of () and {} by incorporating two main factors: a colon and whitespace. The statement is ended with a colon, and whitespace is used (indentation) to describe what takes place in case of the statement.

Another major difference is the lack of semicolons in Python. Semicolons are used to denote statement endings in many other languages, but in Python, the end of a line is the same as the end of a statement.

Lastly, to end this brief overview of differences, let’s take a closer look at indentation syntax in Python vs other languages:


Here is some pseudo-code to indicate the use of whitespace and indentation in Python:

Other Languages

if (x)


if x:
    if y:

Note how Python is so heavily driven by code indentation and whitespace. This means that code readability is a core part of the design of the Python language.

Now let’s start diving deeper by coding these sort of statements in Python!

Time to code!

if, elif, else Statements

if Statements in Python allows us to tell the computer to perform alternative actions based on a certain set of results.

Verbally, we can imagine we are telling the computer:

“Hey if this case happens, perform some action”

We can then expand the idea further with elif and else statements, which allow us to tell the computer:

“Hey if this case happens, perform some action. Else, if another case happens, perform some other action. Else, if none of the above cases happened, perform this action.”

Let’s go ahead and look at the syntax format for if statements to get a better idea of this:

if case1:
    perform action1
elif case2:
    perform action2
    perform action3

Let’s Explore more example in jupyter notebook.

Python for Loops

A for loop is used for iterating over a sequence (that is either a list, a tuple, a dictionary, a set, or a string).

This is less like the for keyword in other programming languages, and works more like an iterator method as found in other object-orientated programming languages.

With the for loop we can execute a set of statements, once for each item in a list, tuple, set etc.

Here’s the general format for a for loop in Python:

for item in object:
_____statements to do stuff

The variable name used for the item is completely up to the coder, so use your best judgment for choosing a name that makes sense and you will be able to understand when revisiting your code. This item name can then be referenced inside your loop, for example if you wanted to use if statements to perform checks.

Let’s go ahead and work through several example of for loops using a variety of data object types. We’ll start simple and build more complexity later on.