Use the spread() function

One principle of tidy data is to change from wide to long; and conversely, long to wide.

Here’s a concrete example:

Using spread()

The first part of the below pre-processing steps include subsetting the original data frame (data) by selecting two countries for comparison (Morocco and Qatar) on specific variables such as: GeoAreaName, TimePeriod, Sex, Type of skill and Value.

Then employing group_by to ensure all rows are unique. The next line is key as it addresses an error that each row must be marked by a unique id key.

Finally, the spread() function allows us to see each countries’ relative performance on various ICT skills. Please consult meta-data for more details.

data %>%
    filter(GeoAreaName=="Morocco" | GeoAreaName=="Qatar") %>% 
    select(GeoAreaName, TimePeriod, Sex, `Type of skill`, Value) %>%
    group_by(GeoAreaName, TimePeriod, Sex, `Type of skill`, Value) %>%
	
    # Error: Each row of output must be identified by a unique combination of keys.
    # rowid_to_column() address this error
	
    tibble::rowid_to_column() %>%
    spread(key = `Type of skill`, value = Value)