Sets in Python are unique data types. Apart from lists, tuples and dictionaries, sets are one of the most well known and sought after data storing variables. Sets unlike lists cannot be sliced or indexed, hence their processing speeds are faster than other data types.
The type error in Python occurs when there is a mismatch between the operator and the operands. For example, if you’re trying to search the elements in a set by using index, the interpreter will raise a type error because sets in Python cannot be indexed.
We will look at what sets are in Python and how type errors are associated with them. we will also go through the possible fixes so that you can avoid type errors when using sets in the future. Let’s get started!
Understanding Sets in Python: Unique Data Storage Structures
Sets are a unique type of data storing structures in Python. A set in mathematics is referred to as a collection of elements or numbers in an organized manner. Sets are represented with curly brackets {} in mathematics as well as in Python.
In programming, sets are one of the most well-known data types used for storing multiple elements or objects. In Python, it is one of the major data-storing variable types among the four.
Sets are immutable in mature, that is, they are unchangeable. They are also unordered, meaning, they cannot be indexed hence individual elements in a set cannot be accessed through their positions.
New elements can be added to existing sets and existing elements can be removed from sets using specific in-built functions. Just like appending elements into a list, sets add new elements at the end of the existing objects since they are unordered.
Elements in sets can be referred through their values. Duplicates are a big “no-no” in sets. There exists no duplicate elements in sets. If two objects are assigned the same value, then only the one appearing first in order from left to right will be considered as an element of the set and the duplicate will be ignored.
Example of a set is:
Our_set={'apples','bananas','oranges'}
Besides using the curly braces to describe sets, the set() constructor is also supported in Python. You can create and explicitly convert a data type into a set using this constructor.
The len() function can be used to determine the length or size of a set in Python.
In the example given below, we first used the add() function to add a new element to our first_set containing numbers. In the second_set, we have removed the last element from the set using the remove() function. These are two of the most important set functions.
In addition to these two functions, we have also demonstrated how the len() function work with sets.
#defining sets
first_set={1,2,3,4}
print("orginal first set=",first_set)
#using add() function
first_set.add(5)
print("modified first set=",first_set)
second_set={"apple",'banana','orange','pears'}
print("Original Second set=",second_set)
#using remove() function
second_set.remove('orange')
print("modified second set=",second_set)
#determining sizes of the first and second sets using the len() function
print("The lengths of the first_set and the second_set are: "+str(len(first_set))+" and "+str(len(second_set))+" respectively.")
The output would be:
orginal first set= {1, 2, 3, 4}
modified first set= {1, 2, 3, 4, 5}
Original Second set= {'apple', 'banana', 'orange', 'pears'}
modified second set= {'apple', 'banana', 'pears'}
The lengths of the first_set and the second_set are: 5 and 3 respectively.
Read more about the different data types in Python by referring to the official documentation.
Fixing the TypeError: ‘set’ object is not subscriptable in Python
When you try to index the elements in a set, you’ll come across a Type error in Python. Type errors in Python are common when the interpreter cannot figure out what it needs to do with a particular type of input about a particular action or function because they do not match the desired type.
Subscriptable means to occupy a particular position or index in a data type. Unlike lists, sets are unordered, meaning that no particular element has a fixed position, hence they cannot be accessed through their addresses.
There are many ways which can help us fix this error. Some of them are given below.
Method 1: Changing the data type of the variable
If you need to access a particular element using its’ position or index, simply convert a set into a list using the list() constructor.
After you’re done performing the required operations, such as appending or changing the position of elements, convert the list back into a set if desired.
#our set
set1={1,2,3,4,5}
#converting the set to list
L=list(set1)
#converting the list back to a set after printing the first element using index.
print("The first element of our original set is=",L[0])
print("After conversion=",L)
print("Before conversion=",set1)
The output of the above code would be:
The first element of our original set is= 1
After conversion= [1, 2, 3, 4, 5]
Before conversion= {1, 2, 3, 4, 5}
Similar: [SOLVED] Type Error: ‘can’t concat bytes to str’ in Python.
Method 2: Using the ‘in’ statement
To check if an element is present inside a set, we can use the ‘in’ statement along with the value of that particular element to make our life easier instead of using indexes.
The code given below demonstrates how we can implement this method.
#our set
set1={1,2,3,4,5}
#checking if an element is in set1 using their values
#using the in statement in addition to if
if 2 in set1:
print("yes!")
else:
print("No")
The output for this program is:
yes!
Do check out: [SOLVED] ‘Unexpected Keyword Argument’ TypeError in Python.
Wrapping Up: Python Sets and TypeError
In this tutorial, we have covered what Python sets are and how they are immutable and unordered. They cannot be indexed like lists which are ordered and can be referenced by their positions. This might raise an exception called type error, since indexing or slicing is unsupported.
There are a couple of ways in which you can bypass this error and index the elements of a set by converting it into other data types. Why do you think people use sets even when lists are available?