One of the most popular and commonly used programming languages today is Python. Be it Data Science, Machine Learning, or any other field of work, most people and organizations across the world are using Python for several purposes. The main aim of this blog is to give you an insight into what Python is and the several Python data types that are available for you to learn, comprehend and make use of for respective purposes. As per Forbes, Python is among one of the top-ranked languages today.
What is Python?
You must have definitely come across Python programming language. However, do you know anything about it like how and where you can use it? Why don’t we start from the beginning and get an overview of this frequently and widely used programming language?
Python is an object-oriented, high-level, and an interpreting language comprising of dynamic semantics. It comprises of built-in high-level data structures, along with the dynamic binding and dynamic typing. Besides making it extremely attractive for Rapid Application Development, you can also make use of it as a glue or a scripting language that helps in connecting the already existing components.
This programming language is simple and extremely easy to learn. Its comprehensive syntax emphasizes not only its readability but also reduces the maintenance cost of the program. Moreover, it supports packages and modules that encourage the reusability and modularity of the code. Also, the extensive, as well as endless library and interpreter of Python, are available in both source and binary forms for free in most well-known platforms. Besides, you can also distribute it at no additional cost.
Let’s get an understanding of its features.
Various Frameworks and Libraries
A great advantage of Python is the large selection of frameworks and libraries it offers. Your opportunity to-market will improve in the event that you influence them since you would not have to manually code the features.
Python libraries are available for a varied range of processes including:
- Machine Learning (ML)
- Data Visualization
- Data Science
- Complex Data Analysis
- Natural Language Processing (NLP)
From libraries like NumPy to even TensorFlow, and so on, Python has it all.
The equivalent is valid for frameworks, which help you in completing your project in Python.
Performance
Perhaps the greatest analysis of Python is the runtime, generally moderate when contrasted with different dialects. Be that as it may, there’s a workaround to this particular test.
At the point when execution takes need, Python enables you to incorporate other, higher-performing dialects into your code. Cython is a genuine case of such an answer. It improves your speed without driving you to modify your whole codebase without any preparation.
Additionally, the priciest asset isn’t CPU time; it’s your engineers’ time. Lessening your opportunity to-market ought to hence consistently outweigh quick runtime execution.
Easy to Maintain
Python is natural to peruse, on the grounds that it looks like real English. This makes the language easy to unravel and keep up. Moreover, Python has unmistakable grammar and doesn’t require the same number of lines of code like Java or C to give you equivalent outcomes.
Reliable Scalability
Adaptability is erratic. No one can tell when your client numbers flood and you wind up organizing the capacity to scale over whatever else.
That is the reason Python is such an ideal decision, with its dependability and versatility. The absolute greatest players on the web, like YouTube, have wagered on Python for that very explanation.
Now that you have and understood a little about Python, let’s dive into what Python data types are and what are some of the most popular data types in Python.
Python Data Types
According to Python data types W3Schools, data types are an integral part of any programming language including Python. According to their definition, you should use Python data types so that variables have the option to adapt and store distinct types or values and data.
To explain to you the term in simpler words, data types in Python GeeksforGeeks mention that they are the categorization or classification of data into various sectors and segments. Their main role is to represent the type of data value that informs you about the several operations you can perform on that particular data or dataset. As you all know, or even if you do not, the data types in Python are technically the classes in the program while the instances or objects, on the other hand, are the variables present in these classes.
Below are the built-in and standard forms of Python data types:
- Numeric – Integer, Float, and Complex Number
- Boolean
- Dictionary
- Set
- Sequence Type – Strings, List, and Tuple
Numeric Data Type
The numeric data type in Python is one of the most commonly used data types. It represents those data that have numeric values such as integers, floating values, and also complex values. In Python, you can define these values or data types like int, float, and complex classes respectively.
Let us now get an understanding of these numeric Python data types or classes:
- Integers: You can represent the integer values in Python using the int class. This data type consists of both positive and negative numbers. However, the integer data type does not include decimal or fraction values. Also, unlike most programming languages, you can use a value of any length, there is no limit.
- Float: You can use the float class in order to represent float values. This value comprises a real number along with a floating-point.
- Complex Numbers: In order to represent complex numbers in Python, you can make use of its complex class. You can specify the complex number in the following format- (Real Number) + (Imaginary Value) j. As an example, consider this value – 2+4j
To determine the data type of any value, you can make use of the type() function.
Boolean Data Type
The boolean data type in Python comprises of two in-built values, that is, either True or False. Those boolean objects or values that are equivalent to True are true values whereas the ones that are equivalent to False are false values. You can use bool in order to denote this class.
‘T’ for True and ‘F’ for False are the only two valid boolean values. In the case of any other inputs, Python will give an error.
Dictionary Data Type
Python’s dictionary data type is an unorganized collection of values of data. The main use of a dictionary is to store data values such as a map. Besides, unlike other Python data types that have the capabilities to hold an element of a single value, dictionary stores a key-value pair. In order to optimize the dictionary more, you need to provide the key-value pair. To separate the key-value pair present in the dictionary, you need to make use of a colon (:) while, in the case of separating each key, you need to use a comma (,).
To create a dictionary in Python, you need to start by placing a series of elements using curly braces ({}) and make use of a comma to separate them. The dictionary comprises of a pair of data values in which on is the Key while the other pair element is the corresponding value of that key or the key: value. You can store any data type in a dictionary and further duplicate the same. However, you are not allowed to repeat the keys of these values which is why these keys have to be immutable.
You can also make use of the in-built dict() function to create a dictionary. If you wish to develop an empty dictionary, you can do so easily by simply placing a set of curly braces with no elements.
Another thing you need to keep in mind in terms of the dictionary is that the keys in a dictionary are case sensitive. Keys with the same name but with distinct cases are different.
Set Data Type
Set data type in Python is another unorganized cluster of data type which is mutable, iterable and does not comprise any duplicate values. The elements order in the given set is generally undefined but it may or may not include several elements. One of the biggest advantages of the set data type is that it comprises an optimized method in order to check if a specific value is available in the set.
You can use the in-built set function to create a set with either a repeatable instance or a sequence by inserting a series of elements in a set of curly braces and using a comma in order to separate them. A set involves only unique and distinct values however, during the time of creating a set, you can also pass several duplicate values. The element order in case of a set is unchangeable and also undefined. Besides that data types of the elements in a set do not have to be the same, you can mix and match a variety of data types and values and pass them in a set.
Sequence Data Type
The sequence data type in python is an organized and ordered collection of either similar or distinct data types. You can use it to store a number of values in an efficient manner. The sequence data types in Python are as follows:
- String
- List
- Tuple
Strings
Strings in Python are arrays that represent Unicode character in the form of bytes. It is more or less a cluster of at least one character inside a set of either single quotes, double quotes, or even triple quotes. Python does not have any character data type like programming languages. A character is basically a single length of the string. You can use the str class to represent a string.
You can create a string in Python with any of the above-mentioned quotes.
List
Just like how you declare arrays in other programming languages, you can do the same with the list in Python. Since it does not necessarily need to always be homogeneous, it is one of the most significant and powerful tools of Python. You can store data types such as strings, integers, and even objects. They are mutable therefore, you can alter then even after you create them.
Python lists are in order and are also definitive. You can index the list elements as per a sequence. The first index in a list begins with a zero (0). All the elements in a list have their definite place that also allows duplication of list elements as all the elements have their credibility and place. You can represent a list in Python using a list class. Also, you can create Python lists by simply placing them in a series inside a set of square braces ([]). You can easily create a list without any need for a built-in function.
Tuple
A tuple is another arranged cluster of Python objects, a lot of like a list. The succession of data values that you can store in a tuple can be of any data type, and you can use integers to index them. The significant distinction between a tuple and a list is that tuples are permanent and immutable while lists are not. Likewise, Tuples are hashable but, lists are most certainly not. In order to represent a tuple, you can use a tuple class.
In Python, you can make tuples by putting succession of data values isolated by ‘comma’ with or without the utilization of brackets for the gathering of the data sequence. Tuples can include any number of components, of any data type (such as strings, list, integers, and so on.). Likewise, you can also make tuples with a single component, yet it is somewhat tricky at times. Having one component in the brackets is not at all adequate, there must be a ‘comma’ training in order to make it a tuple.
Conclusion
This blog mainly helps you to get a brief understanding of the Python programming language and Python data types. Further, you also get to read and comprehend the various data types that Python offers as well as how and when you can easily make use of the same. You can also go through a few Data Types in Python pdf files in order to become more proficient in this object-oriented programming language.
