The correlation does not effect your model using decision trees in a classification problem.
In the theory of decision tree models, you don`t need correlation or check of multicollinearity. Because the split in decision trees is made of entropy/information gain.
The correlation does only check linear dependencies. The same is, when the dataset is highly ...
I believe boxplot or violin plot is a good idea and you could overlay datapoints with a bit of jitter to the former. See below an example in seaborn taken from a relevant question:
import seaborn as sns
import matplotlib.pyplot as plt
tips = sns.load_dataset("tips")
sns.violinplot(x="day", y="total_bill", data=tips, color=&...