Analysis of the data before running into predictions is very important. Understand a few rows and a few columns is very nominal task and we can easily examine the data. However, with a little larger data, suppose 10,000 rows with 50 columns, we really need to do analysis of the data so that we can come to know which factors are going to affect our prediction. Data Analysis with Python is a bit tedious task as we have to prepare the data i.e. cleaning, pre-processing and normalization. We use Seaborn and Matplotlib for our data visualization. But before plotting the graphs, we need to know which columns are inter-related. For that, we need a co-relation matrix which we can create using Python. However, PPS matrix is more better than co-relation matrix. Fig1: Co-relation Matrix of Covid19 dataset Fig2: PPS Matrix of Covid19 dataset It is always a tedious task when we code for Data Analysis. So, we have certain tools available in the market for it like Power BI, Tableau, etc. I have done