Python- Numpy & Pandas Python Programming Language Libraries

Description

Welcome to my " Python: Python Programming with Python project & 100 quizzes " course.

Python | Numpy & Pandas for Python Data Analysis, Data Science, Machine Learning from A-Z with python projects & quizzes

Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis. Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.

Python instructors at OAK Academy specialize in everything from software development to data analysis and are known for their effective, friendly instruction for students of all levels.
Whether you work in machine learning or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn. Python, machine learning, Django, python programming, machine learning python, python Bootcamp, coding, data science, data analysis, programming languages.

Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed upon the premise that there should be only one way (and preferably one obvious way) to do things, a philosophy that has resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing a variety of different tools for programmers suited for many different tasks.

Pandas is an open source Python package that is most widely used for data science/data analysis and machine learning tasks. Pandas is built on top of another package named Numpy, which provides support for multi-dimensional arrays.

Pandas is mainly used for data analysis and associated manipulation of tabular data in DataFrames. Pandas allows importing data from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. data analysis, pandas, numpy, numpy stack, numpy python, python data analysis, python, Python numpy, data visualization, pandas python, python pandas, python for data analysis, python data, data visualization.

Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.

Pandas Pyhon aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language.

Python is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python is one of the most important skills you can learn.

Numpy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Moreover, Numpy forms the foundation of the Machine Learning stack.

NumPy aims to provide an array object that is up to 50x faster than traditional Python lists. The array object in NumPy is called ndarray , it provides a lot of supporting functions that make working with ndarray very easy.

NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.

With this training, where we will try to understand the logic of the PANDAS and NumPy Libraries, which are required for data science, which is seen as one of the most popular professions of the 21st century, we will work on many real-life applications.

The course content is created with real-life scenarios and aims to move those who start from scratch forward within the scope of the PANDAS Library.

PANDAS Library is one of the most used libraries in data science.

Do you want to learn one of the employer’s most requested skills? If you think so, you are at the right place.

We've designed for you "Python: Python Programming with Python project & 100 quizzes” a straightforward course for the Python programming language.

In the course, you will have down-to-earth way explanations of hands-on projects. With my course, you will learn Python Programming step-by-step. I made Python 3 programming simple and easy with exercises, challenges, and lots of real-life examples.

This Python course is for everyone!

My "Python: Learn Python with Real Python Hands-On Examples" is for everyone! If you don’t have any previous experience, not a problem! This course is expertly designed to teach everyone from complete beginners, right through to professionals ( as a refresher).

Why Python?

Python is a general-purpose, high-level, and multi-purpose programming language. The best thing about Python is, that it supports a lot of today’s technology including vast libraries for Twitter, data mining, scientific calculations, designing, back-end server for websites, engineering simulations, artificial learning, augmented reality and what not! Also, it supports all kinds of App development.

No prior knowledge is needed!

Python doesn't need any prior knowledge to learn it and the Ptyhon code is easy to understand for beginners.

What you will learn?

In this course, we will start from the very beginning and go all the way to programming with hands-on examples . We will first learn how to set up a lab and install needed software on your machine. Then during the course, you will learn the fundamentals of Python development like

• Installing Anaconda Distribution for Windows

• Installing Anaconda Distribution for MacOs

• Installing Anaconda Distribution for Linux

• Reviewing The Jupyter Notebook

• Reviewing The Jupyter Lab

• Python Introduction

• First Step to Coding

• Using Quotation Marks in Python Coding

• How Should the Coding Form and Style Be (Pep8)

• Introduction to Basic Data Structures in Python

• Performing Assignment to Variables

• Performing Complex Assignment to Variables

• Type Conversion

• Arithmetic Operations in Python

• Examining the Print Function in Depth

• Escape Sequence Operations

• Boolean Logic Expressions

• Order Of Operations In Boolean Operators

• Practice with Python

• Examining Strings Specifically

• Accessing Length Information (Len Method)

• Search Method In Strings Startswith(), Endswith()

• Character Change Method In Strings Replace()

• Spelling Substitution Methods in String

• Character Clipping Methods in String

• Indexing and Slicing Character String

• Complex Indexing and Slicing Operations

• String Formatting with Arithmetic Operations

• String Formatting With % Operator

• String Formatting With String.Format Method

• String Formatting With f-string Method

• Creation of List

• Reaching List Elements – Indexing and Slicing

• Adding & Modifying & Deleting Elements of List

• Adding and Deleting by Methods

• Adding and Deleting by Index

• Other List Methods

• Creation of Tuple

• Reaching Tuple Elements Indexing And Slicing

• Creation of Dictionary

• Reaching Dictionary Elements

• Adding & Changing & Deleting Elements in Dictionary

• Dictionary Methods

• Creation of Set

• Adding & Removing Elements Methods in Sets

• Difference Operation Methods In Sets

• Intersection & Union Methods In Sets

• Asking Questions to Sets with Methods

• Comparison Operators

• Structure of “if” Statements

• Structure of “if-else” Statements

• Structure of “if-elif-else” Statements

• Structure of Nested “if-elif-else” Statements

• Coordinated Programming with “IF” and “INPUT”

• Ternary Condition

• For Loop in Python

• For Loop in Python(Reinforcing the Topic)

• Using Conditional Expressions and For Loop Together

• Continue Command

• Break Command

• List Comprehension

• While Loop in Python

• While Loops in Python Reinforcing the Topic

• Getting know to the Functions

• How to Write Function

• Return Expression in Functions

• Writing Functions with Multiple Argument

• Writing Docstring in Functions

• Using Functions and Conditional Expressions Together

• Arguments and Parameters

• High Level Operations with Arguments

• all(), any() Functions

• map() Function

• filter() Function

• zip() Function

• enumerate() Function

• max(), min() Functions

• sum() Function

• round() Function

• Lambda Function

• Local and Global Variables

• Features of Class

• Instantiation of Class

• Attribute of Instantiation

• Write Function in the Class

• Inheritance Structure

With my up-to-date course, you will have a chance to keep yourself up-to-date and equip yourself with a range of Python programming skills. I am also happy to tell you that I will be constantly available to support your learning and answer questions.

Do not forget ! Python for beginners has the second largest number of job postings relative to all other languages. So it will earn you a lot of money and will bring a great change in your resume.

What is python?
Machine learning python is a general-purpose, object-oriented, high-level programming language. Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python bootcamp is one of the most important skills you can learn. Python's simple syntax is especially suited for desktop, web, and business applications. Python's design philosophy emphasizes readability and usability. Python was developed on the premise that there should be only one way (and preferably, one obvious way) to do things, a philosophy that resulted in a strict level of code standardization. The core programming language is quite small and the standard library is also large. In fact, Python's large library is one of its greatest benefits, providing different tools for programmers suited for a variety of tasks.

Python vs. R: What is the Difference?
Python and R are two of today's most popular programming tools. When deciding between Python and R in data science , you need to think about your specific needs. On one hand, Python is relatively easy for beginners to learn, is applicable across many disciplines, has a strict syntax that will help you become a better coder, and is fast to process large datasets. On the other hand, R has over 10,000 packages for data manipulation, is capable of easily making publication-quality graphics, boasts superior capability for statistical modeling, and is more widely used in academia, healthcare, and finance.

What does it mean that Python is object-oriented?
Python is a multi-paradigm language, which means that it supports many data analysis programming approaches. Along with procedural and functional programming styles, Python also supports the object-oriented style of programming. In object-oriented programming, a developer completes a programming project by creating Python objects in code that represent objects in the actual world. These objects can contain both the data and functionality of the real-world object. To generate an object in Python you need a class. You can think of a class as a template. You create the template once, and then use the template to create as many objects as you need. Python classes have attributes to represent data and methods that add functionality. A class representing a car may have attributes like color, speed, and seats and methods like driving, steering, and stopping.

What are the limitations of Python?
Python is a widely used, general-purpose programming language, but it has some limitations. Because Python in machine learning is an interpreted, dynamically typed language, it is slow compared to a compiled, statically typed language like C. Therefore, Python is useful when speed is not that important. Python's dynamic type system also makes it use more memory than some other programming languages, so it is not suited to memory-intensive applications. The Python virtual engine that runs Python code runs single-threaded, making concurrency another limitation of the programming language. Though Python is popular for some types of game development, its higher memory and CPU usage limits its usage for high-quality 3D game development. That being said, computer hardware is getting better and better, and the speed and memory limitations of Python are getting less and less relevant.

How is Python used?
Python is a general programming language used widely across many industries and platforms. One common use of Python is scripting, which means automating tasks in the background. Many of the scripts that ship with Linux operating systems are Python scripts. Python is also a popular language for machine learning, data analytics, data visualization, and data science because its simple syntax makes it easy to quickly build real applications. You can use Python to create desktop applications. Many developers use it to write Linux desktop applications, and it is also an excellent choice for web and game development. Python web frameworks like Flask and Django are a popular choice for developing web applications. Recently, Python is also being used as a language for mobile development via the Kivy third-party library.

What jobs use Python?
Python is a popular language that is used across many industries and in many programming disciplines. DevOps engineers use Python to script website and server deployments. Web developers use Python to build web applications, usually with one of Python's popular web frameworks like Flask or Django. Data scientists and data analysts use Python to build machine learning models, generate data visualizations, and analyze big data. Financial advisors and quants (quantitative analysts) use Python to predict the market and manage money. Data journalists use Python to sort through information and create stories. Machine learning engineers use Python to develop neural networks and artificial intelligent systems.

How do I learn Python on my own?
Python has a simple syntax that makes it an excellent programming language for a beginner to learn. To learn Python on your own, you first must become familiar with the syntax. But you only need to know a little bit about Python syntax to get started writing real code; you will pick up the rest as you go. Depending on the purpose of using it, you can then find a good Python tutorial, book, or course that will teach you the programming language by building a complete application that fits your goals. If you want to develop games, then learn Python game development. If you're going to build web applications, you can find many courses that can teach you that, too. Udemy’s online courses are a great place to start if you want to learn Python on your own.

Why would you want to take this course?

Our answer is simple: The quality of teaching.

OAK Academy based in London is an online education company. OAK Academy gives education in the field of IT, Software, Design, development in English, Portuguese, Spanish, Turkish, and a lot of different languages on the Udemy platform where it has over 2000 hours of video education lessons. OAK Academy both increases its education series number by publishing new courses, and it makes students aware of all the innovations of already published courses by upgrading.

When you enroll, you will feel the OAK Academy`s seasoned developers' expertise. Questions sent by students to our instructors are answered by our instructors within 48 hours at the latest.

Video and Audio Production Quality

All our videos are created/produced as high-quality video and audio to provide you the best learning experience.

You will be,

• Seeing clearly

• Hearing clearly

• Moving through the course without distractions

You'll also get:

Lifetime Access to The Course

Fast & Friendly Support in the Q&A section

Udemy Certificate of Completion Ready for Download

Dive in now!

We offer full support, answering any questions.

See you in the " Python: Python Programming with Python project & 100 quizzes " course.

Python | Numpy & Pandas for Python Data Analysis, Data Science, Machine Learning from A-Z with python projects & quizzes

What You Will Learn!

• Python is a computer programming language often used to build websites and software, automate tasks, and conduct data analysis.
• Python is a general-purpose language, meaning it can be used to create a variety of different programs and isn't specialized for any specific problems.
• Whether you work in artificial intelligence or finance or are pursuing a career in web development or data science, Python is one of the most important skills
• Its simple syntax and readability makes Python perfect for Flask, Django, data science, and machine learning.
• Installing Anaconda Distribution for Windows
• Installing Anaconda Distribution for MacOs
• Installing Anaconda Distribution for Linux
• Reviewing The Jupyter Notebook
• Reviewing The Jupyter Lab
• Python Introduction
• First Step to Coding
• Using Quotation Marks in Python Coding
• How Should the Coding Form and Style Be (Pep8)
• Introduction to Basic Data Structures in Python
• Performing Assignment to Variables
• Performing Complex Assignment to Variables
• Type Conversion
• Arithmetic Operations in Python
• Examining the Print Function in Depth
• Escape Sequence Operations
• Boolean Logic Expressions
• Order Of Operations In Boolean Operators
• Practice with Python
• Examining Strings Specifically
• Accessing Length Information (Len Method)
• Search Method In Strings Startswith(), Endswith()
• Character Change Method In Strings Replace()
• Spelling Substitution Methods in String
• Character Clipping Methods in String
• Indexing and Slicing Character String
• Complex Indexing and Slicing Operations
• String Formatting with Arithmetic Operations
• String Formatting With % Operator
• String Formatting With String Format Method
• String Formatting With f-string Method
• Creation of List
• Reaching List Elements – Indexing and Slicing
• Adding & Modifying & Deleting Elements of List
• Adding and Deleting by Methods
• Adding and Deleting by Index
• Other List Methods
• Creation of Tuple
• Reaching Tuple Elements Indexing And Slicing
• Creation of Dictionary
• Reaching Dictionary Elements
• Adding & Changing & Deleting Elements in Dictionary
• Dictionary Methods
• Creation of Set
• Adding & Removing Elements Methods in Sets
• Difference Operation Methods In Sets
• Asking Questions to Sets with Methods
• Comparison OperatorsIntersection & Union Methods In Sets
• Structure of “if” Statements
• Structure of “if-else” Statements
• Structure of “if-elif-else” Statements
• Structure of Nested “if-elif-else” Statements
• Coordinated Programming with “IF” and “INPUT”
• Ternary Condition
• For Loop in Python
• For Loop in Python(Reinforcing the Topic)
• Using Conditional Expressions and For Loop Together
• Continue Command
• Break Command
• List Comprehension
• While Loop in Python
• While Loops in Python Reinforcing the Topic
• Getting know to the Functions
• How to Write Function
• Return Expression in Functions
• Writing Functions with Multiple Argument
• Writing Docstring in Functions
• Using Functions and Conditional Expressions Together
• Arguments and Parameters
• High Level Operations with Arguments
• all(), any() Functions
• map() Function
• filter() Function
• zip() Function
• enumerate() Function
• sum() Function
• max(), min() Functions
• round() Function
• Lambda Function
• Local and Global Variables
• Features of Class
• Instantiation of Class
• Attribute of Instantiation
• Write Function in the Class
• Inheritance Structure
• Pandas is an open source Python package that is most widely used for data science/data analysis and machine learning tasks.
• Pandas is mainly used for data analysis and associated manipulation of tabular data in DataFrames.
• Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
• Pandas Pyhon aims to be the fundamental high-level building block for doing practical, real world data analysis in Python
• Numpy is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices.
• NumPy aims to provide an array object that is up to 50x faster than traditional Python lists.
• NumPy brings the computational power of languages like C and Fortran to Python.

Who Should Attend!

• Anyone who wants to start learning Python bootcamp
• Anyone who plans a career as Python developer
• Anyone who needs a complete guide on how to start and continue their career with Python in data analysis
• And also, who want to learn how to develop ptyhon coding
• People who want to learn python
• People who want to learn python programming
• People who want to learn python programming, python examples
• Anyone who is particularly interested in big data, machine learning
• Those who want to learn the Pandas Library, which is necessary for data science
• Those who want to improve themselves in the field of Python Programming Language and Data science

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