How to statistically prove that a column in a dataframe is not needed
With respect to the other answers i observed your point about having features which are strings, you must first find a way to encode them as numerical features which can then help you with PCA and the problem with the heat-map will be resolved too. Also if your problem is of regression then you can use methods such as L1-Regularization which help you in feature selection and you don't have to remove the features while pre-processing.