Course Content

Introduction to Finance with Python

1. Python Basics

Data Types Basic Operators Functions Operating with Arrays using NumPy Processing Tabular Data with Pandas Challenge: Uploading Financial Data

2. Options Trading

Options Basics Call Options Put Options Black-Scholes Model

3. Time Series Forecasting

Basic Definitions Autoregressive model (AR)Challenge: Autoregressive Model with Moving Average(ARMA) Autoregressive Model with Integrated Moving Average (ARIMA)

Challenge: Uploading Financial Data

Getting data from the web

Now, we are going to show how to get financial data directly from the web.

As an example, we are going to work with stock price data from financial provider Yahoo FInance.

To do so, we need a special library, called yfinance, which could be imported with a code import yfinance as yf.

If we want to see complete financial information, for example, about Amazon, we can use the following code :


              12345
            
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Printing whole information from a dictionary of items
for key, value in GetAmazonInformation.info.items():
        print(key, ":", value)

As we can see, we are using shortened form of a company's name, like 'AMZN' here for Amazon.

The same situation with all other companies, like 'META' for Meta, 'GOOGL' for Google, 'MSFT' for Microsoft, 'NVDA' for Nvidia and so on.

Retrieving stock history

Now we are going to discuss, how can we get historical data with stock prices.

Note, that in further cases, necessary data will be retrieved as a DataFrame object, described into previous chapter.

In case we want to get history of stock prices for a whole period available, we need to use history method:


              12345
            
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Getting stock data for the whole available period
df=GetAmazonInformation.history(period="max")
print(df)

Meanwhile, if we want to get data for a specific period, like 3 month, we should respectively set value of parameter period:


              12345
            
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Getting stock data for last 3 month
df=GetAmazonInformation.history(period="3mo")
print(df)

Other valid values of period parameter: '1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y' and 'ytd'(which stands for 'Year to Date', and practically means period from the beginning of the year to the last date available).

Lastly, if we want to get data for a period with specific starting date and ending date, we need to change parameters start and end respectively:


              1234567
            
import datetime
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Getting stock data for the period from 11th July of 2023 to the 11th July of 2024
df=GetAmazonInformation.history(start = datetime.datetime(2023, 7, 11),
                                  end = datetime.datetime(2024, 7, 11))
print(df)

Task

Swipe to show code editor

In this task you need to:

Get financial data GetNvidiaInformation for Nvidia company;
Get DataFrame df with the history of it's stock prices for the period from the beginning of the current year, till the last available date.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 6

Challenge: Uploading Financial Data

Getting data from the web

Now, we are going to show how to get financial data directly from the web.

As an example, we are going to work with stock price data from financial provider Yahoo FInance.

To do so, we need a special library, called yfinance, which could be imported with a code import yfinance as yf.

If we want to see complete financial information, for example, about Amazon, we can use the following code :


              12345
            
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Printing whole information from a dictionary of items
for key, value in GetAmazonInformation.info.items():
        print(key, ":", value)

As we can see, we are using shortened form of a company's name, like 'AMZN' here for Amazon.

The same situation with all other companies, like 'META' for Meta, 'GOOGL' for Google, 'MSFT' for Microsoft, 'NVDA' for Nvidia and so on.

Retrieving stock history

Now we are going to discuss, how can we get historical data with stock prices.

Note, that in further cases, necessary data will be retrieved as a DataFrame object, described into previous chapter.

In case we want to get history of stock prices for a whole period available, we need to use history method:


              12345
            
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Getting stock data for the whole available period
df=GetAmazonInformation.history(period="max")
print(df)

Meanwhile, if we want to get data for a specific period, like 3 month, we should respectively set value of parameter period:


              12345
            
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Getting stock data for last 3 month
df=GetAmazonInformation.history(period="3mo")
print(df)

Lastly, if we want to get data for a period with specific starting date and ending date, we need to change parameters start and end respectively:


              1234567
            
import datetime
import yfinance as yf
GetAmazonInformation = yf.Ticker("AMZN")
# Getting stock data for the period from 11th July of 2023 to the 11th July of 2024
df=GetAmazonInformation.history(start = datetime.datetime(2023, 7, 11),
                                  end = datetime.datetime(2024, 7, 11))
print(df)

Task

Swipe to show code editor

In this task you need to:

Get financial data GetNvidiaInformation for Nvidia company;
Get DataFrame df with the history of it's stock prices for the period from the beginning of the current year, till the last available date.

Switch to desktop for real-world practiceContinue from where you are using one of the options below

Everything was clear?

Thanks for your feedback!

Section 1. Chapter 6

Switch to desktop for real-world practiceContinue from where you are using one of the options below