Speeding through the intersection
In the previous lesson, you determined why three countries (South Korea, Brunei, and Iran) don't have matching results in the IMF data compared to the World Bank data for Asia. You'll next see the Asian country entries that do overlap as a nice check.
The datasets from the last lesson (asia_wb
, asia_wb_combos
, imf_subset
, and imf_combos
) have been loaded for you. Recall that world_bank_data
was trimmed to only focus on Asian countries and a few columns in the asia_wb
tibble. A few columns were also selected from imf_data
in the imf_subset
tibble. asia_wb_combos
is distinct combinations of iso
and country
in asia_wb
, and imf_combos
is distinct combinations of iso
and country
for imf_subset
.
This exercise is part of the course
Programming with dplyr
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Identify distinct country names for asia_wb
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