Pandas_Cheat_Sheet.pdf

1. Functions: Functions are blocks of reusable code. They are defined using the def keyword. Here's a simple example:

   def greet(name):
       print("Hello, " + name + "!")
   
   greet("John")
   
   

2. Lists: Lists are ordered, mutable sequences. They can contain elements of different types.

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   my_list = [1, 2, 3, "four", 5.0]
   print(my_list[0])  # Accessing elements
   my_list.append(6)  # Modifying the list
   
   

3. Dictionaries: Dictionaries are collections of key-value pairs. They are unordered and mutable.

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   my_dict = {'name': 'John', 'age': 25, 'city': 'New York'}
   print(my_dict['name'])  # Accessing values
   my_dict['age'] = 26    # Modifying values
   
   

4. Tuples: Tuples are ordered and immutable sequences. They are similar to lists but cannot be modified once created.

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   my_tuple = (1, 2, 3)
   print(my_tuple[0])  # Accessing elements
   
   

5. Sets: Sets are unordered collections of unique elements.

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   my_set = {1, 2, 3, 3, 4}
   print(my_set)  # Outputs: {1, 2, 3, 4}
   
   

6. Classes and Objects: Python is an object-oriented language. You can define classes and create objects from those classes.

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   class Dog:
       def __init__(self, name):
           self.name = name
   
       def bark(self):
           print("Woof!")
   
   my_dog = Dog("Buddy")
   my_dog.bark()
   
   

7. Modules and Packages: Python code can be organized into modules, and modules can be grouped into packages. This helps in organizing and reusing code.

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   # module.py
   def say_hello():
       print("Hello from the module!")
   
   # main.py
   import module
   module.say_hello()
   
   

8. File Handling: Python provides various functions for reading from and writing to files.

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   with open('example.txt', 'w') as file:
       file.write('Hello, World!')
   
   

9. Exception Handling: Use try-except blocks to handle exceptions and prevent program crashes.

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   try:
       result = 10 / 0
   except ZeroDivisionError:
       print("Cannot divide by zero!")
   
   

10. List Comprehensions: A concise way to create lists.

    squares = [x**2 for x in range(5)]
    

These are just a few of the essential features in Python. Familiarizing yourself with these concepts will provide a solid foundation for more advanced programming in Python.

1. Generators and Iterators: Generators allow you to create iterators in a more concise way. They are defined using functions with the yield keyword.

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   def countdown(n):
       while n > 0:
           yield n
           n -= 1
   
   for i in countdown(5):
       print(i)
   
   

2. Decorators: Decorators allow you to modify or extend the behavior of functions or methods.

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   def my_decorator(func):
       def wrapper():
           print("Something is happening before the function is called.")
           func()
           print("Something is happening after the function is called.")
       return wrapper
   
   @my_decorator
   def say_hello():
       print("Hello!")
   
   say_hello()
   
   

3. Lambda Functions: Lambda functions are anonymous functions defined using the lambda keyword.

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   add = lambda x, y: x + y
   print(add(2, 3))
   
   

4. List comprehensions with conditionals: You can include conditionals in list comprehensions for more complex filtering.

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   even_squares = [x**2 for x in range(10) if x % 2 == 0]
   
   

5. Map, Filter, and Reduce: These are higher-order functions that operate on lists or other iterables.

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   numbers = [1, 2, 3, 4, 5]
   squared = list(map(lambda x: x**2, numbers))
   evens = list(filter(lambda x: x % 2 == 0, numbers))
   product = functools.reduce(lambda x, y: x * y, numbers)