📦 Exercise Files

To efficiently handle folders, navigate directories, write to files, and run scripts in your JupyterNotebook, use these four magic commands:

✨ %mkdir: Create folders.
✨ %cd: Navigate directories.
✨ %%writefile: Write to files.
✨ %run: Execute external Python scripts.

Exponential smoothing is useful for capturing the underlying pattern in the data.

The tsmoothie library is a fast and efficient Python tool for performing TimeSeries smoothing operations.

🚀 Link to tsmoothie: https://bit.ly/3L8KXky

🤯Python interview questions can cover a broad range of topics depending on the specific role and company.

👀👉Here's a list of some common and important Python interview questions:

1. Basics of Python:
- What are the key features of Python?
- Explain the differences between Python 2.x and Python 3.x.
- How is memory managed in Python?

2. Data Types and Data Structures:
- Describe Python's basic data types.
- Explain lists, tuples, sets, and dictionaries in Python.
- What is the difference between shallow copy and deep copy?

3. Control Structures:
- Explain the difference between if-else and elif statements.
- How does a for loop differ from a while loop?
- What is the use of break and continue statements?

4. Functions and Modules:
- Define a function in Python. How do you pass arguments to a function?
- What are lambda functions and how are they used?
- Explain the use of import and how Python searches for modules.

5. Object-Oriented Programming (OOP):
- What is OOP, and how is it implemented in Python?
- Describe inheritance, encapsulation, and polymorphism.
- What is the purpose of self in Python classes?

6. Exception Handling:
- How do you handle exceptions in Python?
- Explain the use of try, except, finally blocks.

7. File Handling:
- How do you open and read/write a file in Python?
- What is the difference between read() and readline()?

8. Advanced Topics:
- What are decorators in Python?
- Explain generators and iterators.
- Describe the map, filter, and reduce functions.

9. Libraries and Frameworks:
- What are some popular Python libraries used for data analysis?
- Have you worked with any web frameworks in Python (like Django or Flask)?

10. Testing and Debugging:
- How do you perform unit testing in Python?
- What tools are available for debugging Python code?

These questions cover a wide array of Python concepts and are often used to gauge a candidate's familiarity and proficiency with the language.

It's important to not just memorize answers but understand the underlying principles and be able to apply them to real-world problems.