How to select variables based on the mean correlation in a correlation matrix?
There is no universal definition of "strongly correlated" and thus there is no "correct" answer to your question. One approach would be to perform a significance test to determine whether there is strong evidence that the correlations are nonzero. The mathematical details of the test are here, and the relevant Scipy API documentation is here.

However, "probably nonzero" may not be what you're looking for when you say "strongly correlated." If that's the case, you might want to consider why you're interested in finding the strongly correlated variables in the first place. Are you interested in identifying the strongly correlated features for a predictive problem? If so, you'll likely be better off skipping this exercise and starting to experiment directly with learning algorithms. Are you interested in determining what predictor variables cause changes in a certain response variable? In this case, you'll probably want to look into some kind of statistical regression model (probably starting with linear regression) and be very careful about all of the assumptions involved when drawing causal conclusions.