How should I read the following heatmap? I've been playing around with the linear regression, and I was thought that before commencing it's always good to plot an heatmap to see whether there are features that somehow is worth testing for their significance/relationship.
Would you agree with the above?

With that being said, after having refined a tiny bit my data, I obtained the following heatmap:



As you can see I now have two features completely blank. I though in the beginning to some sort of rendering glitch, which is not the case.

In reviewing the dataset, I found out that the features have always the same value across the dataset.

I'd assume this is not being printed out due to the fact this feature has became statistically significant for every feature. 

Would you say this is a correct way of referring to this? Or is there any other way to express this concept?

This is however not the case for the other feature, which contains a mix of numerical value, hence I'm not able to explain.

Can you please advice?
Since the variables isPWKinText and H1_2_Len have the same value for all examples in your dataset they have zero variance and contain no information. There is simply just no inference you can make based on them. That is why they are not relevant and shown blank.  

Please note, that this depends on your dataset, of course. The two variable might just be constant for the examples you are currently looking at. For example, if this is an analysis of your training data maybe your datasplit is just really bad and the validation or test set contains examples for which these variable do show other values. That is something I suggest to double check.