7 Important Concepts In Python Which You Should Know
With a boom in artificial intelligence, data science, and machine learning applications, the demand for Python developers has also increased. Python’s ease of access and readability has made it one of the most popular programming languages today. Switching over to Python can unleash endless possibilities for developers. Here, we have identified some of the most important Python concepts which you should know.
Most online tutorial courses assume that you need to learn all syntaxes in Python before you start doing anything interesting. This may lead to spending months only on Python syntax when what you want to be doing is to analyze the data or build a website or maybe create a drone! So here are the 7 Python concepts that you need to focus on besides the Python syntax while you take up an online Python tutorial-
Variables- object types and scope
Information that can be used for a program is stored in variables and they typically have a name so that they can be referenced in the code. Python supports strings, numbers, lists, sets, tuples, and dictionaries which are standard data types. If you check any online Python tutorial you can read in detail about these data types.
In Python, if you have to declare a variable, you only have to assign a value to it. There is no need for any additional commands. Variables can have local or global scope. One of the most common Python questions asked in an interview is – Mention what are the rules for local and global variables in Python?
Therefore, ensure that you know this concept thoroughly as it forms the basis of your programming.
It allows the user to perform computation on variables. The following are the different types of python operators.
Each operator functions as the name suggests, you can check out the working of these operators in an online Python tutorial. Often in an interview one of the Python questions asked is to define the use of any of the operators. For instance- Mention the use of // operator in Python?
Comments are used to make the code more readable. It helps in explaining the Python code and can also help in preventing execution when testing code. Comments in Python start with a ‘#’. It can be placed at the end of a line, and the rest of the line will be ignored in Python. You can refer to online Python tutorial for usage of comments in detail.
Loops in Python
Repetitive commands or redundant codes can be a nightmare for any programmer. Python uses loops to overcome this problem. The loops allow you to execute a group of statements numerous times. Loops in Python are categorized as –
- For Loop
- While Loop
- Nested Loops
Dictionaries and Sets
Sets and dictionaries in Python are almost identical, except that sets do not contain values actually, it is just a collection of unique keys. Sets are used in doing set operations whereas Python dictionary is a collection that is changeable, unordered, and indexed. The items in a Python dictionary are accessible by referring to its key name.
Therefore, learning the concept of Python dictionaries and sets is essential. If you are taking up an online python tutorial then do learn about Python dictionary with methods, functions, and operations. There are a few in-built dictionary methods in Python which can help you in programming.
Classes and Functions
Python is an object-oriented language, therefore it is important to know the concept of classes thoroughly. A Python class is like a blueprint of an object that provides all the standard features of object-oriented programming. The classes can have custom attributes/ properties and functions. The object-oriented design allows the programmers to define their business model as objects with their required functions and properties.
On the other hand, functions in Python are a sequence of statements that you can execute in your code. It helps in eliminating the repetition of code and make it simpler to debug or find issues. Most importantly, functions make the code more understandable and simpler to manage.
Slicing in Python is most commonly applied to lists and strings. It is a process of taking a subset of any data. To put it simply, slicing enables the programmer to choose what to see and focus on thus aiding in implementing abstractions and readability.
If you're confused between the two statistics languages Python and R and want to know which language is better, check out our article on Python vs R for Data Science.
We hope that you find the above useful. To understand these concepts in detail do go through Python problem sets while you undertake a full-fledged online python tutorial.