# Free Python and Statistics for Financial Analysis

## There are 4 modules in this course

Python is now becoming the number 1 programming language for data science. Due to python’s simplicity and high readability, it is gaining its importance in the financial industry.  The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.

By the end of the course, you can achieve the following using python:

- Import, pre-process, save and visualize financial data into pandas Dataframe

- Manipulate the existing financial data by generating new variables using multiple columns

- Recall and apply the important statistical concepts (random variable, frequency, distribution, population and sample, confidence interval, linear regression, etc. ) into financial contexts

- Build a trading model using multiple linear regression model

- Evaluate the performance of the trading model using different investment indicators

Jupyter Notebook environment is configured in the course platform for practicing python coding without installing any client applications.

# Problem: Implement a Stack using Python

Implement a stack data structure in Python. A stack is a linear data structure that follows the Last-In, First-Out (LIFO) principle, where the last element added to the stack is the first one to be removed.

Your task is to create a Python class called Stack that has the following methods:

push(item): Adds an item to the top of the stack.

pop(): Removes and returns the item from the top of the stack.

peek(): Returns the item currently at the top of the stack without removing it.

is_empty(): Returns True if the stack is empty, and False otherwise.

size(): Returns the number of items in the stack.

You can implement the stack using a list as the underlying data structure.

Here's a basic structure for the Stack class:

class Stack:

def __init__(self):

# Initialize an empty stack

pass

def push(self, item):

# Add item to the top of the stack

pass

def pop(self):

# Remove and return the item from the top of the stack

pass

def peek(self):

# Return the item at the top of the stack without removing it

pass

def is_empty(self):

# Return True if the stack is empty, False otherwise

pass

def size(self):

# Return the number of items in the stack

pass

# What is the purpose of the @property decorator in Python?

A) It marks a method as a property, allowing it to be accessed like an attribute.

B) It defines a new class.

C) It marks a method as static, meaning it can only be called on the class and not on instances of the class.

D) It marks a method as a class method.

A) It marks a method as a property, allowing it to be accessed like an attribute.

# What is the purpose of the __str__ method in a Python class?

A) It defines a new instance variable.

B) It initializes the class object.

C) It specifies the return type of a method.

D) It defines a string representation of the object when using `str()`.  