Stock_Market_Analysis_SQ500_Python

Performed extensive ETL to model the data for predicting whether tomorrow opening price would be high or low than yesterdays closing price Imported yhfinance library to access and download historical market data and used SP500 for our market predcitions. Heavy data cleaning and manipulation was used to make sure that data is clean and stable to perform modelling over it. Dealing with null values was one of it. Ran random forest to see what features/ KPI's are important for stock market prediction. As the data is time series as well, ran a basic ARIMA model for better predcitions.