Full Answer
How to get the stock price from a website using Python?
You start by importing the libraries into Python that you just installed. You then want to get the HTML of the website that you are getting the stock price off of. To do this you use a function called requests.get () that when inputted a URL will go to the server the website is run on and and ask if we can copy its HTML.
What is stock market prediction in Python?
Hello there! Today we are going to learn how to predict stock prices of various categories using the Python programming language. Stock market prediction is the act of trying to determine the future value of company stock or other financial instruments traded on an exchange.
How to get historical stock data in Python?
Now to build something like this first step is to get our historical stock data. We can get our historical stock data using API’s provided as library support in Python. A few of the API’s are mentioned below:
How to get financial data in Python?
Luckily, getting financial data in Python is a breeze with the help of several public APIs, free data sources, and well-developed libraries! Python is often used for algorithmic trading, backtesting, and stock market analysis. In fact, it seems almost the canonical use-case for many tutorials I’ve seen over the years.
Get current stock price in Python
In this article, we have covered how to get the current stock price in Python from Yahoo Finance using two Python libraries, Beautiful Soup, and the Requests library.
Yahoo Finance
Yahoo Finance (finance.yahoo.com) is a media property that provides financial news and data about stock quotes, financial reports, financial summaries, etc. A ticker symbol or stock symbol is used to search for the stock information of a particular company. A stock symbol may consist of letters, numbers, or a combination of both.
Import the packages
The lines of code below import the packages you installed in the previous section.
Use Requests to send an HTTP request
The Requests library is used to make HTTP requests using Python. We use the GET method or verb as we need to fetch the stock data from Yahoo Finance. We call the HTTP GET method on the requests module passing it the URL of the webpage we want to scrape data.
Parse the content using Beautiful Soup
The Beautiful Soup library is used to scrape websites to retrieve data from HTML and XML files. Beautiful Soup creates a parse tree from the given page that makes it easy to search and extract data.
Inspect the page to find the data
To find the stock price we need from the webpage, we need to inspect the webpage. To inspect the HTML page, we need to open the developer tools. There are several ways of opening the developer tools:
What is the Python library called?
It turns out that using the very convenient Python library called yfinance, this task becomes really easy.
What does "close" mean in stock?
Close: the stock price at the end of that day/month/year
Can you use YFinance library?
You can also use the yfinance library to get upcoming earnings events regarding the company.
Do you have to have all the lines of code to get the price of stocks in real time?
You officially now have all the lines of code needed to get the price of stocks in real time.
Is the stock craze going to be bigger in 2021?
It’s 2021 and the stock craze is the biggest it’s ever been. Ever day huge companies are hitting all-time highs which leads the public to buying more stocks in an attempt to cash in. Of those in the public, the majority are headline chasers. They see that X company stock increases by Y% and they immediately invest.
What is get_stock_quote_type_data?
get_stock_quote_type_data — returns a lot of general information about the stock, similar to yfinance ‘s info. Using the method returns the following:
What is get_financial_stmts?
get_financial_stmts — a useful method for getting information on the financial statements of the company
What is YFinance library?
yfinance is a very convenient library, which is my go-to library for downloading stock prices. It was previously known as fix_yahoo_finance. The short history of the library is that is started as a fix to the popular pandas_datareader library. With time, Yahoo Finance changed the API and the connected functionalities were deprecated. That is when fix_yahoo_finance was introduced to once again make downloading data from Yahoo Finance possible. It worked as both a patch to pandas_datareader, and as a standalone library.
What is the advantage of using the Ticker module?
The advantage of using the Ticker module is that we can exploit the multiple methods connected to it. The methods we can use include:
Is Yahoo Finance free to download?
There are many alternatives out there (Quandl, Intrinion, AlphaVantage, Tiingo, IEX Cloud, etc.), however, Yahoo Finance can be considered the most popular as it is the easiest one to access (free and no registration required).
Method 1: Using Yahoo Finance
We can get stock using the yfinance.download () function provided in the yfinance module which is a module for Yahoo’s Finance API. We can download the module using the following command.
Method 2: Using Pandas DataReader
Another way of getting the historical stock data is to use the pandas_datareader library. It also uses Yahoo’s Finance API to load in the data. We can download the module using the following command.
Method 3: Using Quandl
Quandl has hundreds of free and paid data sources, across equities, fixed incomes, commodities, exchange rates, etc. In order to get the access, we need to create an account on Quandl and get an API Key to access the data for free. After that, we need to download the API support quandl library of python using the following command.
2. Loading and Preparation of Data
For the project we will be using the all_stocks_5yrs csv file which includes stock data for 5 years and has seven columns which are listed below.
3. Understanding the Data
From the whole dataset, we will first extract all the unique stock ticks name with the help of unique function. In the dataset, we have 444 different stock names.
4. Creating a new Dataframe and Training data
To make our study easier we will only consider the closing market price and predict the closing market price using Python. The whole train data preparation is shown in the steps below. Comments are added for your reference.
5. Building LSTM Model
The LSTM model will have two LSTM layers with 50 neurons and two Dense layers, one with 25 neurons and the other with one neuron.
6. Compiling the Model
The LSTM model is compiled using the mean squared error (MSE) loss function and the adam optimizer.
7. Testing the model on testing data
The code below will get all the rows above the training_data_len from the column of the closing price. Then convert the x_test data set into the NumPy arrays so that they can be used to train the LSTM model.
8. Error Calculation
RMSE is the root mean squared error, which helps to measure the accuracy of the model.
What is Python used for?
Python is often used for algorithmic trading, backtesting, and stock market analysis. In fact, it seems almost the canonical use-case for many tutorials I’ve seen over the years. Getting financial data in Python is the prerequisite skill for any such analysis.
What is Pandas library?
Pandas is a powerful data science library that stores tabular data into memory in a very efficient manner. It makes the opening, processing, and subsequent saving of data fast and effective. It comes with a range of helper methods, data classes, and in the case of financial data—web APIs!
How to get an API key for Alpha Vantage?
These data are free but not public meaning you need an API key. Such keys can be obtained by registering an account with Alpha Vantage. Entering your name, email, and status (educator, student, investor, etc.) will earn you an API key in a matter of seconds—you don’t even have to confirm your email! Let’s take a look at getting data from this API.
Can you get financial data in Python?
Whether via official APIs, well-supported third-party libraries, or even hacked-together approaches there seems no shortage of OHLC data to be had. These examples showcase why Python has emerged as the defacto programming language for data science —financial data included.
Does Google have a financial API?
As of October 2012 Google no longer offers a financial API service. This news came as a shock to many but was ultimately reflective of many policy changes to public APIs. Google also does not provide financial data via metered APIs, as evidenced by a search on their APIs explorer. The Google Finance API is still available however but only as an Excel-style formula in Google Sheets:
Is historical stock price good in Python?
Getting historical stock prices in Python is all well and good but what is one to do with such data? There are tones of approaches for analyzing OHLC data—allowing one to distill many numbers of useful insights based on expected outcomes and use-case. Below are some projects that can get you started:
Can you use OHLC data in Python?
These are only a few common applications of OHLC financial data in Python. These tutorials details how stock data can be used to identify patterns, correlations, and even predict future prices—all in the comfort of Python! Ultimately the only limitation to use of these data is the analyst’s imagination!
