Data Cleaning and Data Analysis of Big Mart Data Based on Python

In this paper, I am committed to using machine learning to predict the sales of goods based on the sales data of stores. Among them, I firstly understand the meaning of the data set, trying to dig deeply to found out the hidden relationships that are significant for further exploration. Then, for missing value, I filled them with predicted values. As for the categories that can be optimized, I modified them in order to get more accuracy prediction. After that, I used 2 methods which are linear regression and random forest to predict the method and made a comparison between these two methods. Eventually, I used the better method to predict the coefficients of the data.