Visualize Financial Data

Making decisions or deciding your next move in the stock market is all based on data visualization and analysis. In this tutorial, we explain what Data Visualization is, why we use Data Visualization, the most important considerations for Data Visualization, as well as the basics of graphs of different kinds. We are working with pre-read data. I have already read the data and stored it in a CSV file. I will be working with that particular data. Here we have data for Bank of America, JP Morgan, and daily returns for Bank of America. One of the easiest ways to visualize the prices is through a line graph. The line graph is nothing but a line that will connect all the prices and which will help us understand the trend of the prices. To visualize any data we have a package like Matplotlib. In python everything is packaged, we have the Yfinance package to get the data. To visualize we have to import Matplotlib.py plot s plt which is a widely used package for visualization. As you can see the first line is we import this package, now we'll use plt everywhere. We will access the column that we are interested in plotting. We are interested in plotting the close of Bank of America. In the first column to that I just call up plot and that's it even we can ignore those parameters for the timeline and we just run the code from the first cell and as you can see we can easily visualize the closing price of Bank of America. What about other parameters? The size of the figure is very small.