Based on prior knowledge, the feature "ritm_ecg_p_01" represents the ECG rhythm at the time of admission to the hospital. The categories for this feature are "yes" and "no", indicating whether the patient has a sinus rhythm with a heart rate of 60-90 or not.

To analyze the relationship between this feature and the presence of chronic heart failure, we need to examine the distribution of the feature values for each target class.

Here's a possible analysis:

- For the target class "no", the feature values of "yes" suggest that the patient has a sinus rhythm with a heart rate of 60-90 at the time of admission. The absence of "yes" values in the target class "no" indicates that patients without chronic heart failure generally do not have this specific ECG rhythm.
- For the target class "yes", the feature values of "yes" suggest that some patients with chronic heart failure have a sinus rhythm with a heart rate of 60-90 at the time of admission. However, it is important to note that some patients with chronic heart failure may not have this specific ECG rhythm, as indicated by the absence of "yes" values in the target class "yes".

Based on this analysis, we can create the dictionary:

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

In this case, the dictionary shows that the feature value of "yes" is present in both target classes, while the feature value of "no" is only present in the "no" target class. This implies that the presence of the feature value "yes" suggests a higher likelihood of chronic heart failure, while the absence of this feature value does not necessarily rule out chronic heart failure.