```json
{
	"no": ["United-States", "?", "Mexico", "Puerto-Rico", "Jamaica", "Cuba", "Outlying-US(Guam-USVI-etc)", "Holand-Netherlands"],
	"yes": ["United-States", "?", "Peru", "Guatemala", "Dominican-Republic", "Ireland", "Germany", "Philippines", "Thailand", "Haiti", "El-Salvador", "Vietnam", "South", "Columbia", "Japan", "India", "Cambodia", "Poland", "Laos", "England", "Taiwan", "Italy", "Canada", "Portugal", "China", "Nicaragua", "Honduras", "Iran", "Scotland", "Ecuador", "Yugoslavia", "Hungary", "Hong", "Greece", "Trinadad&Tobago", "France"]
}
```
In this analysis, I have considered the relationship between the feature "native-country" and the task of whether the person earns more than $50,000 per year.

From the available data, the values of the feature "native-country" that are present for the target class "no" (earning less than $50,000) are ["United-States", "?", "Mexico", "Puerto-Rico", "Jamaica", "Cuba", "Outlying-US(Guam-USVI-etc)", "Holand-Netherlands"]. These indicate the countries of origin for individuals who earn less than $50,000 per year. However, it's important to note that there is missing data represented by "?".

The values of the feature "native-country" that are present for the target class "yes" (earning more than $50,000) are ["United-States", "?", "Peru", "Guatemala", "Dominican-Republic", "Ireland", "Germany", "Philippines", "Thailand", "Haiti", "El-Salvador", "Vietnam", "South", "Columbia", "Japan", "India", "Cambodia", "Poland", "Laos", "England", "Taiwan", "Italy", "Canada", "Portugal", "China", "Nicaragua", "Honduras", "Iran", "Scotland", "Ecuador", "Yugoslavia", "Hungary", "Hong", "Greece", "Trinadad&Tobago", "France"]. These indicate the countries of origin for individuals who earn more than $50,000 per year. Similar to the target class "no", there is missing data represented by "?".

It's worth noting that some of the countries in the feature "native-country" may not have a significant impact on the target variable, as the number of individuals from those countries might be very small in the dataset.