You would use a parallel coordinate plot for multivariate analysis. Combine it with the following additional aesthetics:
- Variables 1-40 on the x axis
- 0-100 on the y axis
- Line by Observation number
- color or trellis/facet by Country
Using PCA or k-means would be a good solution if all your variables had differing scales or different data types. But since the observations follow similar scales and are fewer groups (2 countries), the Parallel coordinate plot is pretty easy to read, so no need for dimensionality reduction.
You should use boxplots if it is important to compare the summary or overall behavior of country 1 to country 2 for all variables. PCP is better at giving you insights at the level of each individual point or observation.
Also side note on terminology:
graph as a term is often interpreted as network data type of graph, you would get better search results if you use
plot for relational data.