Predicting-the-closing-stock-price-of-APPLE-using-LSTM

Time Series Analysis: A Hands-On Guide Using Pandas and Matplotlib with Yahoo Finance Data Time Series data is a series of data points indexed in time order. Time series data is everywhere, so manipulating them is important for any data analyst or data scientist. In this project, we will discover and explore data from the stock market, particularly some technology stocks (Apple, Amazon, Google, and Microsoft). We will learn how to use yfinance to get stock information, and visualize different aspects of it using Seaborn and Matplotlib, and finally, we will look at a few ways of analyzing the risk of a stock, based on its previous performance history. Getting the Data The first step is to get the data and load it to memory. We will get our stock data from the Yahoo Finance website. Yahoo Finance is a rich resource of financial market data and tools to find compelling investments. To get the data from Yahoo Finance, we will be using yfinance library which offers a threaded and Pythonic way to download market data from Yahoo. Check this article to learn more about yfinance: Reliably download historical market data from with Python