![]() ![]() For this example, I have provided a basic correlation dataset which is in a CSV file. ![]() I leave this as a food for thought for you, the Aspiring Data Scientist, to do a more detailed Exploratory Data Analysis.Īnalyze the 12th Standard Percentages with Graduation Percentages. Plotting correlations with Python is a relatively straight-forward affair. A Data Scientist should have the inquisitiveness to explore and investigate. The above statements are just hypotheses. Likewise, the weak correlation may be because the data is a mix of MBA Specialization in Finance, Marketing, HR, and Business Analytics.The weak correlation between MBA Grades and Graduation Percentages maybe because the Graduation Degree is a mix of B.COM, B.E., B.M.S, etc.A student who has secured very good percentages in the 10th standard is very likely to get good percentages in the 12th standard also. ![]() You’ll then learn how to calculate a correlation matrix with the pandas library. Each point represents the values of two variables. You’ll learn what a correlation matrix is and how to interpret it, as well as a short review of what the coefficient of correlation is. Scatterplots show many points plotted in the Cartesian plane.
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