By definition, a correlation is a statistical measure that indicates the extent to which two or more variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel; a negative correlation indicates the extent to which one variable increases as the other decreases.

Since correlation matrix is symmetric, it is redundant to visualize the full correlation matrix as a heat map. Instead, visualizing just lower or upper triangular matrix of correlation matrix is more useful. We will use really cool NumPy functions, Pandas and Seaborn to make lower triangular heatmaps in Python. Let us load the packages needed.

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