Based on my prior knowledge, frequent premature atrial contractions on ECG at the time of admission to the hospital could indicate a higher risk of chronic heart failure. Therefore, it is likely that the feature "n_r_ecg_p_02" would show a positive relationship with the presence of chronic heart failure.

To analyze the relationship between the feature "n_r_ecg_p_02" and the presence of chronic heart failure, we can examine the frequency of each category in the dataset for both the "no" and "yes" target classes.

Let's create a dictionary that captures the possible values of the feature "n_r_ecg_p_02" for each target class:

```json
{
	"no": ["no"],
	"yes": ["no", "yes"]
}
```

Note that since the feature "n_r_ecg_p_02" is a categorical variable with categories "no" and "yes", we include these possible values for each target class. However, it's important to mention that this is a simplified analysis, and there may be other variables and considerations that should be taken into account for a more comprehensive analysis.