Based on my prior knowledge, premature atrial contractions (PACs) on an electrocardiogram (ECG) can be an indicator of certain cardiac conditions. Therefore, it is possible that the presence or absence of premature atrial contractions on ECG at the time of admission to the hospital (feature n_r_ecg_p_01) could have a relationship with the presence or absence of chronic heart failure (target variable).

To analyze the relationship, we can examine the frequency distribution of the feature values for each target class (chronic heart failure = yes or no). By comparing the distribution patterns, we can determine whether there is any apparent association between the feature and the presence of chronic heart failure.

To generate the dictionary, we will identify the possible values of the feature n_r_ecg_p_01 for each target class: "no" and "yes". For the values that appear in both classes, we will include them in both lists.

Here is the dictionary for the given feature and task:

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

Since the feature only has two possible values ("no" and "yes"), both classes have the same set of values for n_r_ecg_p_01.