Python Operations

Operator	Description
+	addition
-	subtraction
*	multiplication
/	division
**	exponentiation

We have already seen a few of Python’s arithmetic operators, but there are a few on this list that may be new to you.

Numeric Operations

6 + 5.7

11.7

15 - 7

8

4.5 * 4

18.0

2 ** 3

8

2.2 ** 5

51.53632000000002

Let’s apply these to the Python types we have learned and observe the results.

These operators act as expected on numeric types.

An int plus a float results in a float.

And the subtraction of 2 values of type int results with a type int.

Multiplication with a float and an int will result in a float as well.

Exponents can be calculated with ** and applied with int as well as float data types.

Bool

True + True 

2

True * 4

4

False * 2 + True

1

False + 4

4

We saw that addition, subtraction, multiplication, and exponential operations work as expected with numeric values but let’s check out what happens with the other data types.

What happens when we try to add up bool values?

We see that True values are cast as a value of 1, and False values are cast as 0 when they are added together.

Str

'The monster under my bed' + ' is named Mike' 

'The monster under my bed is named Mike'

'The monster under my bed' - ' is named Mike' 

TypeError: unsupported operand type(s) for -: 'str' and 'str'

Detailed traceback: 
  File "<string>", line 1, in <module>

'The monster under my bed' / ' is named Mike' 

TypeError: unsupported operand type(s) for /: 'str' and 'str'

Detailed traceback: 
  File "<string>", line 1, in <module>

Strings react rather interestingly with the addition operator.

For instance, when we add strings, we add the sequence from one end to the other. This is also called concatenation.

And we cannot multiply, divide or subtract two strings.

'The monster under my bed' + 1200

TypeError: can only concatenate str (not "int") to str

Detailed traceback: 
  File "<string>", line 1, in <module>

'The monster under my bed' + str(1200)

'The monster under my bed1200'

'The monster under my bed' * 3

'The monster under my bedThe monster under my bedThe monster under my bed'

We saw that we can operate on float and int values together, but what about str and numeric values?

Adding a string to an integer does not work unless we first cast the integer to a string.

What about the multiplication of a string by an integer?

This will repeat the string by the number you are multiplying.

In this case, the string 'The monster under my bed' is repeated 3 times.

We can multiply strings, and it concatenates the strings together! Since we multiplied by 3, the string is repeated 3 times.

List

list1 = [1, 2.0, 3, 4.5] + ['nine', 'ten', 'eleven', 'twelve']
list1

[1, 2.0, 3, 4.5, 'nine', 'ten', 'eleven', 'twelve']

[1, 2.0, 3, 4.5] - [3, 5, 2, 1]

TypeError: unsupported operand type(s) for -: 'list' and 'list'

Detailed traceback: 
  File "<string>", line 1, in <module>

[1, 2.0, 3, 4.5] * [5, 6, 7, 8]

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[15], line 1
----> 1 [1, 2.0, 3, 4.5] * [5, 6, 7, 8]

TypeError: can't multiply sequence by non-int of type 'list'

How about with other data types like lists, tuples and dictionaries?

If we add lists, similarly to strings, the lists concatenate together to create a single list containing the elements of both lists.

Other operators, like subtraction and multiplication, are not supported when working with lists.

Boolean Operators

Operator	Description
x == y	is x equal to y?
x != y	is x not equal to y?
x > y	is x greater than y?
x >= y	is x greater than or equal to y?
x < y	is x less than y?
x <= y	is x less than or equal to y?
x is y	is x the same object as y?
x and y	are x and y both true?
x or y	is at least one of x and y true?
not x	is x false?

When we’ve filtered our data, we’ve seen different Boolean operators, but we have some new ones here for you.

Let’s explore them.

'dogs' == 'cats'

False

6 < 7

True

(6 < 7) and ('dogs' == 'cats')

False

(6 < 7) or ('dogs' == 'cats')

True

Let’s start with 2 base statements;

• dogs and cats are not equal, so we get a False and
• 6 < 7 is True

We can combine them to explore the and, or and not operators.

We can check if both statements are True using the keyword and.

In this case, since both statements are not True, combining them with and will evaluate to False.

On the other hand, the or operator checks if at least one of the statements are True and since 6 < 7 is a True statement, the or statement evaluates to True.

Since one statement is true, the combined “or” statement is True.

not ('dogs' == 'cats')

True

not  (6 < 7)

False

We know that ('dogs' == 'cats') is False, so a not operator gives us a True because it inverts the Boolean value.

While we know (6 < 7) is True the statement not (6 < 7) produces a False.

How can we translate all this to dataframes now?

Have you ever wondered why we can do summary statistics on some columns and not others? We are going to explore this in the next section.

Seeing if the statement is False will result in a False output since (6 < 7) is True.

Let’s apply what we learned!