Based on prior knowledge, ventricular contractions on ECG at the time of admission to the hospital (n_r_ecg_p_03) can be related to chronic heart failure. Ventricular contractions on ECG may indicate abnormalities in the heart's electrical conductivity, which could be a sign of heart failure.

To analyze the relationship between n_r_ecg_p_03 and the presence of chronic heart failure, we need access to the data containing information on myocardial infarction complications and whether chronic heart failure is present or not.

Once we have the data, we can examine the distribution of n_r_ecg_p_03 categories ('no' and 'yes') for the two target classes ('chronic heart failure' and 'no chronic heart failure'). By comparing the distribution of categories for each target class, we can determine if there is any association between n_r_ecg_p_03 and chronic heart failure.

Here is an example of what the dictionary might look like:

```json
{
	"no": ["no", "no", "no"],
	"yes": ["yes", "yes", "yes"]
}
```
In this example, the feature n_r_ecg_p_03 has only two possible values, 'no' and 'yes'. For the target class 'no chronic heart failure', the values of n_r_ecg_p_03 are all 'no', indicating that no ventricular contractions on ECG were observed. For the target class 'chronic heart failure', the values of n_r_ecg_p_03 are all 'yes', indicating the presence of ventricular contractions on ECG.

Note: The actual values in the dictionary may vary depending on the data. This is just an example to demonstrate the format.