The exploratory data analysis

Since we have worked extensively with the S&P 500 stock data from Kaggle, we are going to be using that dataset in order to create our application. The dataset can be found here: https://www.kaggle.com/camnugent/sandp500/data.

The first step is to read the data into Jupyter Notebook and understand what the data looks like. This can be done using the code shown here:

#Import packages

import pandas as pd

#Read the data into the notebook

df = pd.read_csv('all_stocks_5yr.csv')

#Extract information about the data

df.info()

This renders the output shown in this screenshot:

This sheds information on the number of rows the dataset has, the data types of each column, the number of variables, and any missing values.

The next step is to understand the kind of information contained in all the columns of your dataset. We can do this by using the...