I solved a problem no one in the entire data analytics world could solve.
Globally, it is written that correlation measures are designed for numerical data and assume a linear relationship between variables.
However, when dealing with categorical data, which includes non-numeric values like colors, gender, or product categories, traditional correlation may not be directly applicable.
I’ve addressed this challenge.
Watch the tutorial (How to do Correlation with Categorical Data) here:
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