Python data Types

Python is one of the in-demand programming languages. Each variable in Python holds a value, and all values are stored as data types. Simply put, data types are categorizations of different items. It represents the kind of value that tells what operations can be performed on a particular data.

In this article, we will learn about the different data types that are built using Python and how they are used.

Python Standard Data Types

1. Numeric
2. Boolean
3. Sequence
4. Dictionary
5. Set

These data types are built-in in Python. The latest version of Python is Python 3, which is what is being considered for this post.

1. Numeric

Python uses three kinds of data types to categorize numbers. This means that there are three sub-categories within the numeric data type. They are Integers, Floats, and Complex.

a) Integers

All positive, negative, and zeros are part of integers. But only whole numbers can be classified as integers. So 1,-2, and 78475997758 would be integers, but 2.5 and ⅘ are not. There are no limits to the number of integers in Python, so they can go up to any number of digits.

Example:

a = 10
print(a, "is of type", type(a))
Output: 5 is of type <class ‘int’>

Integers can be used for various simple calculations which make use of whole numbers. For example, if you want to count something, you can use the multiplication action and calculate the total number of a particular object.

b) Float

Numbers having decimals are a part of the float data type. So numbers such as 2.4, 5.0, and 3.4857 are a part of the Float data type.

Example:

b = 5.5
print(b, "is of type", type(b))
Output:  5.5 is of type <class ‘float’> 

Float can be used for more complex calculations in software. For example, if you wish to calculate distance from speed and time, you will be able to do that using Float. Unlike Integers, there is a limitation on the number of floats. It is limited and differs from system to system. So a number that is not covered by your system will be represented by “INFINITY” or “INF”

c) Complex

In the Complex data type, there are real and imaginary components. For example, 6 + 7j is a Complex, where 6 is a real/whole number, and 7j has J, which is an imaginary component.

Example:

c = 6+2j
print(c,"is a type",type(c))
Output: (6+2j) is a type <class ‘complex’>

If you are looking to try out these data sets in a project, check out this post for some fun beginner-friendly ideas.

2. Sequence

Sequences are collections of items arranged in a particular order. The items in the sequence may be referred to by their index number, for example, s[0] and s[1]. Sequence indexes in Python do not begin at 1 but at 0. There are several types of sequences in Python that are built-in:

a) String

Strings - as the name suggests - are a sequence of data types, generally in a textual format. Single, double, or triple quotes can be used to represent strings. Triple quotes are used when there are multiple lines in a string. Strings cannot be modified or updated once they are declared. There are various other functions that you can perform under strings. Some are:

I. The len() function is used to determine a string's length.
II.  The Print(String1*5) can be used to repetitively use a string.
III. The operator + can be used to concatenate different strings together.

b) Lists

Lists are another data type that is very regularly used for various functions. Lists can be created easily by adding elements in a square bracket [ ]. Creating lists in Python is easy as any kind of information can be collated into a list, and it does not require a set pattern. If you want to access individual items in a list, you can use the index number. An index number is a number allotted to every element in a list, starting from 0 (Zero). A list can be modified and updated after its creation.

c) Tuples

Tuples are very similar to lists. Except that, in Tuples, you cannot modify and update it once it is created. Tuples can be created with any kind of data type and can integrate other data types within it as well. This means a string and a list can be a part of a Tuple. Tuples are created with the use of a comma. You can collate tuples in parentheses, but it is not mandatorily required. Accessing elements within a tuple is the same as accessing elements in a list. They make use of Index Numbers as well.

3. Boolean

Data types with two built-in values make use of Boolean. These two values are: True and False. This interesting Python function was not present initially but was added later. This data type is extremely useful for functions with different possibilities based on situations.

For example, if you want to create a scenario where it rains, you want to carry an umbrella; otherwise, you don’t want to. These kinds of functions can be created with the help of Boolean.

The If function in Python is used a lot along with Boolean. Remember to use capital T and F in True and False. Otherwise, Python will show an error.

Example:

a = 550
b = 440
if b > a:
print("b is greater than a")
else:
print("b is not greater than a")
Output:  b is not greater than a

4. Dictionary

Dictionaries are a widely used feature in Python for those who work with large sets of data. In the dictionary, you can assign a key to each data (a value) and use the key to retrieve that particular data.

Example:

Dict = {1:'World',2.'Beautiful',3.'Rainbow'}
print(Dict)
Output: {1: ‘World’, 2: Beautiful, 3: ‘Rainbow’}
To retrieve the data, you will have to do the following:
print(Dict[2])
Output: Beautiful

5. Set

A set is a collection of data with no duplication. Various operations like difference, intersection, union, etc. These operations help identify common and different elements in a set of data. Some important functions in Set are:

1. Frozen Set: Frozen set creates an immutable set, which means no modifications can be made
2. Add/Remove: These functions add or remove elements from the set.
3. Union: It combines all elements of sets.
4. Difference: It finds the different elements in sets.
5. Intersection: It finds the common elements in a set.

Example:

thisset = {"World", "beautiful", "Sky"}
print(this set)
Output:
{"World", "beautiful", "Sky"}

Conclusion

Now that you know about data types and their uses, you need to practice their implementation. Build Python projects and gain expertise in the field. If you need inspiration, here are some Python projects for beginners that you can try!

Furthermore, if you're interested in learning Python from scratch with the help of industry experts, enroll in the Python Programming Certification Course by Board Infinity and get certified!