Python Tutorial

This Python tutorial helps you to learn the course in the best possible way. Here, we provide multiple examples on each topic to learn Python programming language. So you can easily understand these topics. It is an object-oriented Programming language, which is sturdy and the fastest growing language in the current situation.

Python programming language is a general purpose high-level language that is structural, procedural, and object-oriented programming. Like most programming languages, Python code supports classes, static methods, inheritance, etc., and this tutorial page covers everything. And the most crucial part is that it supports modules and packages which encourage code reusability in a program workflow.

I like the Python language’s syntax structure, which removes traditional flower brackets, semicolons, and punctuation. These changes make the code simple and easy to read/understand.

Being a C# experienced programmer, it impressed me with its simple syntax. I must write many lines in C# or Java to get the same result. Its simple syntax rules and less coding drive the users to learn Python. First, we introduce the basics and follow the advanced topics.

Why Learn Python programming language?

Here are some reasons that are not limited to learning Python programming language.

  1. It is trendy because it’s easy to learn code for beginners.
  2. It has a simple syntax (like a spoken language) that makes people understand without effort. Because of this, newbies can quickly start working on simple Python programs or even understand the complex codes written by professionals.
  3. The most versatile language I have ever come across. We can use it for script purposes, web development, data analysis, reporting, and many more.
  4. It’s open-source (free) and supports cross-platform so that you can run this on Mac, Windows, Linux, and other platforms.
  5. Use this language to develop both Windows and web applications.
  6. The kind of resources it has, including materials, forums, and libraries that support this Python development environment, is unimaginable.
  7. Moreover, it has various libraries or modules that support Data Scientists in analyzing and visualizing data.
  8. Because of all the above features, the interpreter helps with rapid application development.

Python Operators Tutorial

It is the best language to learn for people new to programming and experience with other languages. The course’s first step is installing Python programming language on your operating system. If not installed by default.

After the installation, open cmd or terminal and check whether it is there or not. On this page, we used the default IDE for all the examples. After that, however, you can choose your favorite Free/Paid code editors.

Once the Python installation is completed, you can start learning this tutorial, from basic operators to Numpy and pandas modules. And this language supports the following operators. So use this section to learn the basics of this programming.

  1. Install IDE
  2. Arithmetic Operators
  3. Assignment Operators
  4. Bitwise Operators
  5. Comparison Operators
  6. Logical Operators

Python Flow Control Statements

Generally, flow control statements contain a condition followed by a block of code. The condition always returns either True or false. Based on the result, the flow control statement will execute the block of code.

If True, the true statements will execute. Otherwise, False statements execute or exit from a control flow statement. This Python tutorial section covers all of them.

  1. If Else Statement
  2. Nested If Statement
  3. Elif Statement
  4. While Loop
  5. For Loop
  6. Break Statement
  7. Continue Statement

Python Object Types

Within the whole Python page, this section is the most important one to learn. It covers all the object Types, and each one is explained with multiple examples.

  1. Dictionary
  2. datetime
  3. Difference between Dictionary copy and = operator
  4. Sets
  5. Strings
  6. Tuples
  7. Lists
  8. List Comprehensions
  9. Lambda
  10. Introduction and Types of Functions
  11. Iterators
  12. Files
  13. Directory
  14. Array

OOPS

This Python course section helps to learn object-oriented programming.

  1. Classes and Objects
  2. Class Methods
  3. Inheritance
  4. Method Overriding
  5. Static Methods

Python SQL Server

Some queries we can use on SQL Server are Connect to SQL, Create Database, Select Records from Table, Select Sorted Table Records, Top 10 records, and Where Clause.

Built-in Functions

The Python interpreter has many built-in functions to learn. Please follow these links to view the available reference methods list.

  1. Math functions
  2. String methods
  3. List methods
  4. dictionary methods
  5. set Functions

Apart from the above built-in methods, String Concat, String length, and Substring are the two frequently asked questions, so follow the above links to learn them.

Python Common Functions tutorial

Below shown are the standard functions for all the objects. You can use these functions on Lists, Strings, Tuples, sets, and Dictionary objects.

  1. len
  2. max
  3. map
  4. print
  5. sort and sorted
  6. range
  7. zip

Dates

  1. strftime
  2. strptime
  3. timedelta

Tuple Functions

  1. index

Python Data Science

Like any other programming language, it is excellent with all the bells and whistles. However, with the introduction of the Numpy module and other popular data science libraries, it has become trendy. That includes Pandas, SciPy, and matplotlib have become the heart of Data Science and machine learning precisely for Data scientists.

These libraries made this ordinary language the most powerful in the current data science and machine learning world.

Python NumPy Module

The NumPy module is an open-source data science module for machine learning. It provides various functions to perform math operations on N-dimensional array objects for basic understanding.

  1. Numpy Array and Functions
  2. Generate Random Array
  3. Numpy Array Shape
  4. Numpy concatenate
  5. Random Number Generator
  6. Numpy random rand
  7. numpy random randn
  8. random randint

Pandas

Please refer to the Charts Data to understand the data. We use it to plot charts using Pandas and matplotlib libraries for data science.

  1. Series
  2. DataFrame
  3. Convert Dictionary to Pandas DataFrame
  4. Convert List To Pandas DataFrame
  5. Pandas plot charts

matplotlib module

This Python machine learning module is nothing but importing the packages to learn data science, web development, and programming.

  1. matplotlib Bar Chart
  2. matplotlib Histogram
  3. matplotlib Pie Chart
  4. matplotlib Scatter Plot

Examples

The following tutorial page contains the basic and advanced Python programs with examples.

  1. Programming Examples

Please refer to the Official Website to learn more about the libraries and their built-in functions.