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

Based on the given feature, it appears that the feature `n_r_ecg_p_01` represents the presence or absence of premature atrial contractions on the electrocardiogram (ECG) at the time of admission to hospital. The feature is a categorical variable with two possible categories: "no" and "yes".

To analyze the relationship between this feature and the task of determining if the patient shows chronic heart failure, we can examine the distribution of the feature for each target class. Since the feature values are already binary, we can simply list the possible values for each target class.

In this case, both target classes have only one possible value for the feature `n_r_ecg_p_01`. For the class "no" (indicating no chronic heart failure), the feature value is "no". For the class "yes" (indicating presence of chronic heart failure), the feature value is "yes".