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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf
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_Python Bootcamp_ From Zero to Pro in a Short Time_.pdf

  1. "Python Basics Course" is a beginner-friendly book that covers the basics of Python programming as well as more advanced concepts such as working with data, creating visualizations, and building web applications. The book is designed to be a hands-on guide, with numerous exercises and projects to help readers practice and apply what they've learned. The book covers topics such as: ● Installing Python and running Python code ● Basic data types (strings, lists, dictionaries, etc.) ● Control flow (if-else statements, for and while loops) ● Functions ● Object-oriented programming ● Working with data (reading and writing files, working with CSV files, etc.) ● Creating visualizations with Python ● Building web applications with Django The book is geared towards beginner programmers, but it is also suitable for those with some programming experience who are new to Python. It is a great resource for those who want to learn the basics of Python programming quickly and efficiently. Installing Python and running Python code Installing Python and running Python code is a simple process. Here are the steps to install Python and run Python code on a Windows, Mac, or Linux operating system: 1. Download the latest version of Python from the official Python website (https://www.python.org/downloads/).
  2. 2. Run the installer and follow the prompts to install Python on your computer. Make sure to select the option to add Python to your system's PATH environment variable. This will allow you to run Python from the command line. 3. To verify that Python has been installed successfully, open a command prompt or terminal window and type "python" (without the quotes). If Python is installed correctly, you should see the Python prompt (>>>). 4. To run Python code, you can write your code in a text editor and save it with a .py file extension. For example, if your code is saved in a file called "hello.py", you can run it by typing "python hello.py" in the command prompt or terminal window. 5. You can also run Python code interactively by typing it directly into the Python prompt (>>>). 6. Some IDEs have inbuilt python interpreter and you can run your python code by just running the file inside the IDE. 7. You can also use Jupyter notebook Installing Python and running Python code detailed Installing Python: 1. Go to the official Python website (python.org) and download the latest version of Python for your operating system. 2. Run the installer and follow the prompts to install Python on your computer. Running Python code: 1. Open the command prompt or terminal on your computer. 2. Type "python" and press enter to start the Python interpreter.
  3. 3. You can now enter Python commands and see the results immediately. Alternatively, you can create a Python script file with a .py extension and run it by typing "python [filename].py" in the command prompt or terminal. You can also use integrated development environment (IDE) like PyCharm, IDLE, Spyder, Jupyter Notebook, etc. to run your python code. It provides a more user-friendly interface and additional features like debugging, code completion, and version control. Explain Basic data types (strings, lists, dictionaries, etc.) In Python, there are several basic data types that are commonly used to store and manipulate data. These include: 1. Strings: A string is a sequence of characters. You can create a string by enclosing characters in single or double quotes. For example: ○ "Hello, World!" ○ 'Hello, World!' 2. Integers: An integer is a whole number (positive or negative) without a decimal point. For example: ○ 5 ○ -3 3. Floats: A float is a number with a decimal point. For example:
  4. ○ 3.14 ○ -2.5 4. Lists: A list is an ordered collection of items. Lists are created by placing a comma-separated sequence of items inside square brackets. For example: ○ [1, 2, 3, 4, 5] ○ ['apple', 'banana', 'orange'] 5. Dictionaries: A dictionary is an unordered collection of key-value pairs. Dictionaries are created by placing a comma-separated sequence of key-value pairs inside curly braces. For example: ○ {'name': 'John', 'age': 30} ○ {1: 'one', 2: 'two', 3: 'three'} 6. Tuples: A tuple is an ordered collection of items. Tuples are similar to lists, but they are immutable, meaning their values cannot be changed once created. Tuples are created by placing a comma-separated sequence of items inside parentheses. For example: ○ (1, 2, 3, 4, 5) ○ ('apple', 'banana', 'orange') 7. Booleans: A boolean value represents a true or false value. The two boolean values in Python are True and False. These are some of the basic data types in Python. Each data type has its own properties and methods that can be used to manipulate and analyze data. Examples of using the basic data types in Python:
  5. Strings: # concatenating strings name = "John" age = 30 print("My name is " + name + " and I am " + str(age) + " years old.") # string indexing name = "John" print(name[0]) # prints "J" # string slicing name = "John" print(name[1:3]) # prints "oh" # string methods name = "John" print(name.upper()) # prints "JOHN" print(name.replace("J", "B")) # prints "Bon"
  6. Lists: # creating a list fruits = ['apple', 'banana', 'orange'] # accessing elements in a list print(fruits[0]) # prints "apple" # modifying elements in a list fruits[1] = 'mango' print(fruits) # prints ['apple', 'mango', 'orange'] # adding elements to a list fruits.append('kiwi') print(fruits) # prints ['apple', 'mango', 'orange', 'kiwi'] # removing elements from a list fruits.remove('mango')
  7. print(fruits) # prints ['apple', 'orange', 'kiwi'] Dictionaries: # creating a dictionary person = {'name': 'John', 'age': 30, 'gender': 'male'} # accessing elements in a dictionary print(person['name']) # prints "John" # modifying elements in a dictionary person['age'] = 35 print(person) # prints {'name': 'John', 'age': 35, 'gender': 'male'} # adding elements to a dictionary person['city'] = 'New York' print(person) # prints {'name': 'John', 'age': 35, 'gender': 'male', 'city': 'New York'} # removing elements from a dictionary
  8. del person['city'] print(person) # prints {'name': 'John', 'age': 35, 'gender': 'male'} Tuples: # creating a tuple numbers = (1, 2, 3, 4, 5) # accessing elements in a tuple print(numbers[0]) # prints 1 # modifying elements in a tuple # raises TypeError: 'tuple' object does not support item assignment numbers[1] = 6 # adding elements to a tuple # raises TypeError: 'tuple' object has no attribute 'append' numbers.append(6)
  9. # removing elements from a tuple # raises TypeError: 'tuple' object doesn't support item deletion del numbers[2] Booleans: # creating a boolean variable is_student = True # using a boolean variable in a conditional statement if is_student: print("You are a student.") else: print("You are not a student.") # negating a boolean variable is_student = False print(not is_student) # prints True
  10. here are some more examples of using Python to solve simple problems: 1. Calculator # take input from the user num1 = float(input("Enter a number: ")) num2 = float(input("Enter another number: ")) # take the operation from the user operation = input("Enter an operation (+, -, *, /): ") # perform the operation if operation == "+": result = num1 + num2 elif operation == "-": result = num1 - num2 elif operation == "*": result = num1 * num2 elif operation == "/":
  11. result = num1 / num2 else: result = "Invalid operation" # print the result print(result) 2. FizzBuzz # iterate through the range of numbers for i in range(1, 101): if i % 3 == 0 and i % 5 == 0: print("FizzBuzz") elif i % 3 == 0: print("Fizz") elif i % 5 == 0: print("Buzz") else: print(i)
  12. 3. Palindrome Checker # take input from the user word = input("Enter a word: ") # convert the word to lowercase word = word.lower() # check if the word is a palindrome if word == word[::-1]: print("The word is a palindrome.") else: print("The word is not a palindrome.") 4. Factorial # take input from the user num = int(input("Enter a number: "))
  13. # initialize the result variable result = 1 # calculate the factorial for i in range(1, num+1): result *= i # print the result print("The factorial of", num, "is", result) 5. Prime Number Checker # take input from the user num = int(input("Enter a number: ")) # check if the number is prime if num > 1: for i in range(2, num):
  14. if (num % i) == 0: print(num, "is not a prime number.") break else: print(num, "is a prime number.") else: print(num, "is not a prime number.") Control flow (if-else statements, for and while loops) Control flow in Python refers to the order in which the statements in a program are executed. The two main control flow statements in Python are if-else statements and loops. If-else statements: An if-else statement is used to perform different actions based on different conditions. The basic syntax for an if-else statement is: if condition: # code to be executed if condition is true else: # code to be executed if condition is false For example:
  15. x = 5 if x > 0: print("x is positive") else: print("x is negative") Loops: Python provides two types of loops: for loops and while loops. For loops: A for loop is used to iterate over a sequence (such as a list, tuple, or string) and execute a block of code for each item in the sequence. The basic syntax for a for loop is: for variable in sequence: # code to be executed for each item in the sequence For example: for i in range(5): print(i)
  16. While loops: A while loop is used to repeatedly execute a block of code as long as a certain condition is true. The basic syntax for a while loop is: while condition: # code to be executed while condition is true For example: x = 5 while x > 0: print(x) x -= 1
  17. It's important to be careful when using loops and make sure that the loop's stopping condition will eventually be met, otherwise the loop will run indefinitely and cause an infinite loop. Functions In Python, a function is a block of organized, reusable code that is used to perform a specific task. Functions are useful for breaking down a large program into smaller, more manageable pieces. Functions can also be used to avoid repeating the same code multiple times. To define a function in Python, you use the keyword def, followed by the function name, a set of parentheses, and a colon. The code inside the function is indented. The basic syntax for defining a function is: def function_name(parameters): # code to be executed
  18. For example: def greet(name): print("Hello, " + name + "!") greet("John") #prints "Hello, John!" Functions can also take zero or more parameters, and they can also return a value using the ‘return ‘ statement. def add(a,b): return a+b result = add(2,3) print(result) # prints 5 Functions can also have default parameter values, so that the user does not need to specify a value for that parameter. def greet(name, greeting = "Hello"):
  19. print(greeting + ", " + name + "!") greet("John") # prints "Hello, John!" greet("John", "Hi") # prints "Hi, John!" You can also use the *args and ‘**kwargs’ to pass a variable number of arguments to a function. ‘*args’ allows you to pass a variable number of non-keyword arguments to a function and ‘**kwargs’ allows you to pass a variable number of keyword arguments to a function. def my_function(*args, **kwargs): for arg in args: print(arg) for key, value in kwargs.items(): print(key, ":", value)
  20. my_function(1, 2, 3, 4, name="John", age=22) Functions are a fundamental concept in Python and are used extensively in many Python programs. They help to organize and structure code, make it more readable, and increase reusability. Object-oriented programming Object-oriented programming (OOP) is a programming paradigm that is based on the concept of "objects", which can be thought of as instances of
  21. a class. A class is a blueprint for an object, and it defines the properties and methods that an object of that class will have. In Python, you can define a class using the keyword class, followed by the class name, and a colon. The code inside the class is indented. The basic syntax for defining a class is: class ClassName: # properties and methods For example: class Dog: def __init__(self, name, breed): self.name = name self.breed = breed def bark(self):
  22. print("Woof!") Here __init__ is a special method called a constructor. It's used to initialize the object's properties when it's created. Once you've defined a class, you can create an object (or instance) of that class using the class name followed by parentheses. dog = Dog("Fido", "Golden Retriever") print(dog.name) # prints "Fido" dog.bark() # prints "Woof!" OOP has many concepts like inheritance, polymorphism, encapsulation. Inheritance is the ability of a class to inherit properties and methods from another class. Polymorphism is the ability of an object to take on multiple forms. Encapsulation is the practice of hiding the internal details of an object and making it accessible only through its methods. OOP is widely used in Python and in many other programming languages. It helps to organize and structure code, make it more reusable, and make it easier to reason about and understand.
  23. Working with data (reading and writing files, working with CSV files, etc.) In Python, working with data often involves reading and writing files, as well as working with CSV files (comma-separated values). Reading and writing files: Python provides several ways to read and write files. The simplest way to read a file is to use the built-in open() function, which returns a file object that can be used to read the file. Once you have the file object, you can use the read() method to read the entire contents of the file, or the readline() method to read one line at a time. file = open("example.txt", "r") print(file.read()) file.close() To write to a file, you can use the open() function with the mode w or a which stands for write and append respectively. file = open("example.txt", "w") file.write("Hello World!")
  24. file.close() Working with CSV files: Working with CSV files: CSV stands for comma-separated values, and it is a common file format for storing data. Python provides the csv module that provides functionality to read and write CSV files. The csv.reader object can be used to read a CSV file and the csv.writer object can be used to write to a CSV file import csv # Reading a CSV file with open('example.csv', newline='') as csvfile: reader = csv.reader(csvfile) for row in reader: print(row)
  25. # Writing a CSV file with open('example.csv', 'w', newline='') as csvfile: writer = csv.writer(csvfile) writer.writerow(['Name', 'Age']) writer.writerow(['John', '22']) You can also use the pandas library which provides powerful data manipulation and analysis capabilities. It makes working with CSV files easy, as you can read and write CSV files using pandas.read_csv() and pandas.to_csv() functions respectively. import pandas as pd #Reading a CSV file df = pd.read_csv("example.csv") #Writing a CSV file
  26. df.to_csv("example.csv", index=False) These are some of the ways to work with data in Python, specifically reading and writing files, and working with CSV files. There are many other ways to work with data in Python and different libraries for specific data formats and data manipulation tasks. Creating visualizations with Python There are several libraries in Python that can be used to create visualizations, including Matplotlib, Seaborn, and Plotly. Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK. Seaborn is a library for making statistical graphics in Python. It is built on top of Matplotlib and provides a high-level interface for drawing attractive and informative statistical graphics. Plotly is a Python library that is used to create interactive visualizations. It allows you to create plots, graphs, and maps using Python and then share them online.
  27. Pandas and Numpy are also used along with these libraries for handling the data and doing the required calculations. You can refer to the documentation of these libraries for more information on how to use them for creating visualizations. Building web applications with Django Django is a popular, high-level web framework for building web applications with Python. It is a Model-View-Controller (MVC) framework that follows the "Don't Repeat Yourself" (DRY) principle and encourages the use of reusable code. To start building a web application with Django, you will first need to install it. You can install Django using pip by running the command pip install Django. Once Django is installed, you can create a new project by running the command django-admin startproject projectname. This command will create a new directory named projectname that will contain the basic file structure for a Django project.
  28. The main components of a Django project are: ● models.py: where you define the structure of the data in your application (e.g. the fields and properties of a "Blog" model). ● views.py: where you define the logic for handling requests and returning responses to the user (e.g. the code that retrieves a list of all blog posts from the database and sends it to a template to be rendered). ● urls.py: where you define the URLs for your application and map them to views. Django also comes with an automatic admin interface that allows you to manage your data through a web interface. You can activate it by creating a superuser and then adding path('admin/', admin.site.urls) to your urls.py. Django also has built-in support for templates, which are used to separate the presentation of a web page from the logic that generates the content. Django also support RESTful API development, with the help of Django REST framework. There are many resources available for learning Django, including the official Django documentation (https://docs.djangoproject.com/) and various tutorials and books on the subject.
  29. Django is a powerful and versatile web framework that can be used to build a wide range of web applications, from small personal projects to large enterprise applications.
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