Based on prior knowledge, the feature "ritm_ecg_p_01" represents the ECG rhythm at the time of admission to the hospital. It has two possible categories: "yes" and "no", which indicate whether the ECG rhythm is sinus with a heart rate of 60-90 or not.

To analyze the relationship between this feature and the presence of chronic heart failure, we will examine the distribution of the "ritm_ecg_p_01" values for each target class.

Let's create the dictionary:

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

Since the feature "ritm_ecg_p_01" directly indicates the ECG rhythm at the time of admission, there is no need for additional analysis. We can directly map the feature values to their respective target classes: "no" for "no" and "yes" for "yes".

It is important to note that even though there might be other possible values for "ritm_ecg_p_01", we don't have information about them and they are not necessary for determining the presence of chronic heart failure. Thus, only the known values are included in the dictionary.