This blog will cover the Q&As of Python for Data Science (AI/ML) and Data Engineer Training covering Introduction to Python, Objects & Data Structure Basics. This blog will help you to clear your concepts with Objects and Data Structures Basics: List, Tuple, Set, and Dictionaries
We also covered hands-on Lab 1, Lab 2, Lab 3, Lab 4, Lab5, Lab 6, and Lab 7 out of our 25+ extensive labs.
So here are some Q&As of Day 1 & Day 2 live session from Module 1: Introduction to Python & Module 2: Objects & DS basics.
>Introduction To Python
Python is an interpreted, interactive, object-oriented programming language. It has a lot of modules, dynamic typing, very high-level dynamic data types, and classes. It supports multiple programming paradigms beyond object-oriented programming, such as procedural and functional programming.
If you are new to Python, then I would suggest you check our blog on Python For Beginners and Python For Data Science
Q1: What are the key features of Python?
A: Some of the key features are:
- Easy to learn and use: Because Python’s syntax is straightforward and generally similar to the English language, it is considered to be an easy language to learn.
- Expressive: With the help of Python we can perform complex tasks using just a few lines of code, and it is easy. For example, a Hello world!! is simply one line: print(“Hello World!!”).
- Interpreted Language: Python is an interpreted language, meaning that a Python program is executed line by line which makes debugging easy and portable.
- Cross-platform language: Python can run equally on Windows, Linux, UNIX, macOS, etc, making the language portable.
- Free and open-source: It is free and available to the general public, which you can download at python.org.
- Object-oriented language: Python is an object-oriented programming language, using classes and objects. Python also allows functionality like inheritance polymorphism and encapsulation.
Q2: How do I install Python?
A: Python requires about 25 MB of disk space, so make sure that you have enough space. After installing, Python requires an additional 90 MB of space.
- You can download Python here
- Click “Download Python 3.9.7”.
- Scroll down and click “[your operating system] 64-bit installer”.
- After clicking the button, follow the directions of the installer, and you’re done!
Q3: What is an IDE?
A: An IDE (Integrated Development Environment) is a program dedicated to software development. In this case, we are looking for an IDE dedicated to python development. Below is the Lifecycle of IDE. Some features of an IDE include:
- An editor designed to handle code
- Build, execution, and debugging tools
- Some form of source control
Q4: What are the best Python IDEs?
A: A good IDE for a Python environment offers certain important features: save and reload your code files, run code from within the environment, debugging support, syntax highlighting, and automatic code formatting.
General IDEs with Python support:
- Eclipse + PyDev
- Sublime Text
- Atom
Python-specific editors and IDEs:
- PyCharm
- Spyder
- Jupyter
Q5: Is Python a good language for beginning programmers?
A: Yes, It is still common to start students with procedural and statically typed languages such as Pascal, C, or a subset of C++ or Java. Students are choosing Python as their first language.
- Python has a very easy and consistent syntax and a large standard library and, most importantly, using Python in a beginning programming course lets students concentrate on important programming skills such as problem decomposition and data type design.
- With Python, students can be quickly introduced to basic concepts such as loops and procedures.
- They can probably even work with user-defined objects in their very first course.
Q6: What are the applications of Python?
A: Python is used in various software domains some application areas are given below:
- Web and Internet Development
- Games
- Scientific and computational applications
- Language development
- Image processing and graphic design applications
- Enterprise and business applications development
- Operating systems
- GUI based desktop applications
Q7: What are Jupyter Notebooks? How to set up Jupyter notebook Environment?
A: Jupyter Notebook is a web-based interactive computational environment for creating Jupyter notebook documents that supports several languages like Python, R, etc., and is largely used for data analysis, data visualization, and more.
You can set up Jupyter notebook by first installing Anaconda and then using the anaconda command prompt to open the Jupyter notebook. You can check the step-by-step guide to install Jupyter Notebook.
Q8: What is a code in python?
A: In computer programming, computer code refers to the set of instructions, or a system of rules, written in a particular programming language (i.e., the source code). It is also the term used for the source code after it has been processed by a compiler and made ready to run on the computer (i.e., the object code).
Q9: What is the difference between Jupyter & Anaconda?
A: Anaconda is a Python prepackaged distribution of Python which contains a number of Python modules and packages, including Jupyter.
Jupyter is a way of working with Python inside a virtual “notebook” and is quite popular in Data Science. It gives you a way to combine code, images, plots, notes, etc. so you essentially tell a story–how did I draw this conclusion from that data, and so on.
Q10: What is a library?
A: In general, a library is a collection of books or is a room or place where many books are stored to be used later. Similarly, in the programming world, a library is a collection of precompiled codes that can be used later on in a program for some specific well-defined operations. Other than pre-compiled codes, a library may contain documentation, configuration data, message templates, classes, values, etc.
Now that we are introduced to Python, let’s look at the technical terminologies.
>Objects and Data Structure Basics
An Object is an instance of a Class. A class is like a blueprint while an instance is a copy of the class with actual values.
An object consists of the following three categories :
- State: It is represented by the attributes of an object. It also reflects the properties of an object.
- Behavior: It is represented by the methods of an object. It also reflects the response of an object to other objects.
- Identity: It gives a unique name to an object and enables one object to interact with other objects.
>Python Variables
Variables are containers for storing data values. A variable is created the moment you first assign a value to it. Variables do not need to be declared with any particular type, and can even change type after they have been set.
> Data Types
Data types are the classification or categorization of data items. It represents the kind of value that tells what operations can be performed on a particular data. Since everything is an object in Python programming, data types are actually classes and variables are instances (object) of these classes.
Variables can store data of different types, and different types can do different things.
Q11: What are the common built-in data types in python?
A: Built-in data types include:
- Numeric
- Sequence
- Boolean
- Set
- Dictionary
Q12: How to check the datatype of a variable in Python?
A: You can determine the variable datatype by using the type() method. Python type() is an inbuilt method that returns the class type of the argument(object) passed as a parameter. You place the variable inside of a type() function, and Python returns the data type.
>Data Structures
Python has four basic inbuilt data structures namely Lists, Dictionary, Tuple, and Set
Q13: What is a List?
A: Lists in Python are one of the most versatile collection object types available.
- It is defined as an ordered collection of items. The order of elements is an inherent characteristic that remains constant throughout the life of the list.
- Lists are mutable.
- Methods return a string or subset of the list or modify the list to add or remove components Written as var[index], index refers to order within the set.
- List items are indexed, the first item has index [0], the second item has index [1], etc. You can step through lists as part of a loop.
Q14: What is Tuple?
A: A tuple is a built-in data structure in Python that is an ordered collection of objects. Unlike lists, tuples come with limited functionality.
- Tuples cannot be modified, added, or deleted once they’ve been created.
- They are normally written inside parentheses () to distinguish them from lists.
- It contains heterogeneous elements.
- Since tuples are immutable, their length is fixed. To grow or shrink a tuple, a new tuple must be created.
Q15: What is the difference between list & tuple?
A: The key difference between the two is that while lists are mutable, tuples on the other hand are immutable objects. This means that lists can be modified, appended, or sliced on the go but tuples remain constant and cannot be modified in any manner.
Q16: What is Set?
A: A set is an unordered collection with no duplicate elements. Set objects also support mathematical operations like union, intersection, difference, and symmetric difference.
- Basic uses include membership testing and eliminating duplicate entries.
- {} are used to represent a set. Objects placed inside these brackets would be treated as a set.
- Unlike tuples, sets are mutable – they can be modified, added, replaced, or removed.
Q17: What are Dictionaries?
A: Dictionary is a non-homogeneous data structure that stores key-value pairs and is represented by { }.
- Allows you to identify values by a descriptive name instead of the order in a list.
- The Keys are unique and are unordered unless explicitly sorted.
- The main operations on a dictionary are storing a value with some key and extracting the value given the key.
Related References
- An Introduction To Python For Microsoft Azure Data Scientist | DP-100
- Python For Data Science: Why, How & Libraries Used
- Introduction to Artificial Neural Network in Python
- Natural Language Processing with Python
- Data Scientists vs Data Engineers vs Data Analyst
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