Based on the feature description, the feature "n_r_ecg_p_01" represents the presence or absence of premature atrial contractions on an electrocardiogram (ECG) at the time of admission to the hospital. 

To analyze the relationship between this feature and the task of determining whether the patient has chronic heart failure, we can examine the distribution of the feature values for each target class.

Here is a possible analysis:

- For the target class "no" (indicating no chronic heart failure):
  - n_r_ecg_p_01 = "no": This indicates that there are no premature atrial contractions present on the ECG at the time of admission. It is likely that this is a common occurrence for patients without chronic heart failure.
  - n_r_ecg_p_01 = "yes": This indicates that there are premature atrial contractions present on the ECG at the time of admission. It is possible that in some cases, patients without chronic heart failure may also have this condition, but it could be less common.

- For the target class "yes" (indicating chronic heart failure):
  - n_r_ecg_p_01 = "no": This indicates that there are no premature atrial contractions present on the ECG at the time of admission. It is not clear how often this occurs in patients with chronic heart failure. It could be an indication that the condition is not always associated with premature atrial contractions.
  - n_r_ecg_p_01 = "yes": This indicates that there are premature atrial contractions present on the ECG at the time of admission. It is possible that this is a common occurrence in patients with chronic heart failure, indicating a potential relationship between the two variables.

Based on this analysis, we can create the following dictionary:

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

Please note that the values in the dictionary are presented as strings in lists, and each target class has a list of values for the feature. The dictionary includes all possible values for the feature within each target class.