Making Inference from a Correlation Heatmap
Assuming you're using df.corr(), the results from a heatmap are Pearson correlation coefficients which can be thought of as "the explainability between two arrays." 

An effect score closer to 0 translates to there being no relationship. A score closer to 1 or -1 is a positive or negative relationship. A perfect score of 1 is a direct correlation.

Additionally, I would caution against taking action using these values without testing the normalcy/distribution of your data.