Friday, March 17, 2023

Learn Python Language - My Journey to learn python

 

Learn Python Language


I am learning python and also writting the guide for beginers, here is my journey learning python. Come read and learn with me.

Let's start.

Python is a popular programming language used for a wide range of applications, from web development and data science to machine learning and artificial intelligence. Here are some of the basics that you can start with:

Installation: You will need to install Python on your computer to get started. You can download the latest version of Python from the official website: https://www.python.org/downloads/

Basic Syntax: Python has a simple and easy-to-understand syntax that makes it a great language for beginners. You will learn about variables, data types, operators, and control structures such as if/else statements, loops, and functions.

Data Structures: Python provides built-in data structures such as lists, tuples, and dictionaries that allow you to store and manipulate data in your programs.

Input and Output: You will learn how to read input from the user and write output to the console or files.

Object-Oriented Programming: Python supports object-oriented programming, which allows you to organize your code into classes and objects.

Modules and Packages: Python has a vast library of modules and packages that you can use to extend the functionality of your programs.

Error Handling: You will learn how to handle errors and exceptions in your programs to make them more robust.

Debugging and Testing: Debugging and testing are crucial parts of software development. You will learn how to use debugging tools and write unit tests to ensure that your code works as expected.

There are many resources available online for learning Python, including video tutorials, online courses, and books. You can start with the official Python documentation or online courses such as Codecademy or Coursera.



What is relation between python and anaconda?

 

 

Python and Anaconda are related but they serve different purposes.

Python is a programming language that provides a syntax and a set of tools to create software, scripts, and applications.

Anaconda is a data science platform that includes Python and many data science-related libraries such as NumPy, Pandas, Matplotlib, and Scikit-learn. Anaconda provides a distribution of Python, which is bundled with a collection of data science packages, and an environment manager to create isolated environments for different projects.

In other words, Anaconda is a Python distribution that provides a complete data science environment for developers, while Python itself is just a programming language that can be used for a wide variety of purposes beyond data science.

By using Anaconda, you can install and manage different versions of Python along with data science-related packages and libraries, which can simplify the setup of your data science projects. Additionally, Anaconda provides an environment manager, which enables you to create isolated environments for different projects, making it easy to manage dependencies and avoid conflicts between different packages.

Overall, Python is the programming language, while Anaconda is a distribution of Python that includes data science-related packages and an environment manager to help manage different environments for different projects.



Should I install python first or anaconda to start learning python. what do you recommend?

 

If you are new to Python and want to start learning the language, I would recommend installing Anaconda first. Anaconda provides a complete data science platform that includes Python and many popular data science libraries, making it easy to get started with Python for data analysis and scientific computing.

With Anaconda, you can install multiple versions of Python and different packages and libraries, including popular data science packages such as NumPy, Pandas, and Matplotlib, without having to worry about compatibility issues or conflicts between different packages. Additionally, Anaconda includes an environment manager, which allows you to create isolated environments for different projects, making it easy to manage dependencies and avoid conflicts between packages.

Once you have installed Anaconda, you can use the Anaconda Navigator interface to launch Python and other data science tools, or you can use the command-line interface to launch Python directly.

However, if you prefer to start with a simpler and more lightweight installation, you can install Python directly from the official Python website and then add the packages and libraries you need as you go. This approach requires more manual setup and management of packages and dependencies but can be a good option for those who want more control over their installation.

  

 

What to do first after installing anaconda.?

 

After you have installed Anaconda, the first thing you should do is to launch the Anaconda Navigator, which is a graphical user interface (GUI) that allows you to manage your Anaconda installation and launch different data science applications.

To launch the Anaconda Navigator, you can either search for it in your computer's applications or launch it from the Anaconda Prompt. To launch it from the Anaconda Prompt, simply open the Anaconda Prompt and type anaconda-navigator followed by Enter.

Once you have launched the Anaconda Navigator, you can explore the different data science applications that are available, including Jupyter Notebook, Spyder, and RStudio. You can also use the Navigator to create and manage different environments for different projects.

If you're new to Python, I would recommend starting with Jupyter Notebook, which is a web-based interactive development environment (IDE) that allows you to write, run, and share Python code in a notebook format. Jupyter Notebook is a popular tool for data analysis and scientific computing, and it's a great way to get started with Python.

To launch Jupyter Notebook from the Anaconda Navigator, simply click on the "Launch" button next to the Jupyter Notebook icon. This will open Jupyter Notebook in your default web browser, and you can start working with Python code right away.

 
Ok I have launched Jupyter notebook what's next?

 Having launched Jupyter Notebook, you can start using it to write and run Python code.

Jupyter Notebook allows you to create and edit notebooks that contain code, text, and multimedia elements such as images and videos. Each notebook consists of a series of cells, which can contain either code or markdown text.

To create a new notebook, click on the "New" button in the top right corner of the Jupyter Notebook interface and select "Python 3" or any other Python kernel of your choice. This will open a new notebook with an empty code cell.

You can then start writing Python code in the cell, and then run it by pressing "Shift + Enter" or by clicking the "Run" button in the toolbar. Jupyter Notebook will execute the code in the cell and display the output below the cell.

You can also add new cells to the notebook by clicking the "+" button in the toolbar, or by using the keyboard shortcut "Esc + B" to insert a new cell below the currently selected cell.

As you continue to work with Jupyter Notebook, you'll discover many other features and capabilities, such as importing and using Python libraries, plotting data using Matplotlib, and working with data using Pandas.


A small example for writing a python code in Jupyter?

 

Here's a simple example of how to write Python code in Jupyter Notebook:

In Jupyter Notebook, create a new notebook by clicking on "New" in the top right corner of the screen and selecting "Python 3".

In the first cell of the notebook, type the following code:

print("Hello, World!")

Run the code by clicking the "Run" button in the toolbar or by pressing "Shift + Enter".

You should see the output "Hello, World!" printed below the code cell.

That's it! This is a simple example of how to write and run Python code in Jupyter Notebook. You can use Jupyter Notebook to write more complex code and to explore data using Python's data analysis and visualization libraries, such as Pandas and Matplotlib.


You wrote your first ever code in python with your help. Move to a few more examples but not difficult ones

 

Get started with Python. Here are a few more examples of simple Python code snippets that you can try in Jupyter Notebook:

Compute the sum of two numbers:

Python Code is as follows:

a = 5

b = 7

 c = a + b

 print(c)

 

In this code, we first assign the values 5 and 7 to variables a and b, respectively. We then compute the sum of a and b and store the result in a new variable c. Finally, we print the value of c, which should be 12.

 

Compute the average of three numbers:

 

Python Code is as follows:

x = 3

 y = 5

z = 7

avg = (x + y + z) / 3

print(avg)

 

In this code, we first assign the values 3, 5, and 7 to variables x, y, and z, respectively. We then compute the average of these three numbers by adding them together and dividing by 3, and store the result in a new variable avg. Finally, we print the value of avg, which should be 5.

 

Print a list of even numbers:

Python Code is as follows:

for i in range(10):

if i % 2 == 0:

print(i)

In this code, we use a for loop to iterate over the numbers from 0 to 9. For each number i, we check if it's even by computing i % 2. If the remainder is 0, then i is even, so we print it using the print() function. The output should be a list of even numbers from 0 to 8.

I hope these examples help you continue your journey with Python!


Let’s try writing python code in Jupyter

I tried writing following code in Jupyter:

a=3

b=5

d=3+5

print (D)

 

When I entered run button, I got following error, (also refer screenshot below for error)

“NameError Traceback (most recent call last) ~\AppData\Local\Temp\ipykernel_9744\2746299901.py in <module> 2 b=5 3 d=3+5 ----> 4 print (D) NameError: name 'D' is not defined

 



 

 

 

Reason for Error

 

This error is occurring because you are trying to print the variable D, which has not been defined. In Python, variable names are case-sensitive, which means that D is not the same as d.

In your code, you have defined the variables a, b, and d, but not D. When you try to print D, Python raises a NameError because it doesn't recognize the name.

To fix this error, you should change print(D) to print(d), like this:

 

Tell me some basic commands of python

Sure, here are some basic commands in Python:

print(): Used to print output to the console.

Example: print("Hello, world!")

input(): Used to take input from the user through the console.

Example: name = input("What is your name? ")

if/else statements: Used to create conditional logic in your code.

Example:

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if x > 10: print("x is greater than 10") else: print("x is less than or equal to 10") 

for loops: Used to iterate over a collection of items.

Example:

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for i in range(10): print(i) 

while loops: Used to create a loop that continues until a certain condition is met.

Example:

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i = 0 while i < 10: print(i) i += 1 

def keyword: Used to define functions in Python.

Example:

pythonCopy code

def add_numbers(x, y): return x + y 

These are just a few of the many basic commands available in Python.





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