This question is about tidy temporal data. Below are the data on military expenditure for different countries

head(expenditure)

## # A tibble: 6 × 4
##   Entity      Code   Year military_expenditure
##   <chr>       <chr> <dbl>                <dbl>
## 1 Afghanistan AFG    1970              5373185
## 2 Afghanistan AFG    1973              6230685
## 3 Afghanistan AFG    1974              6056124
## 4 Afghanistan AFG    1975              6357396
## 5 Afghanistan AFG    1976              8108200
## 6 Afghanistan AFG    1977              8553767

To compare expenditure counts of Australia and Germany between 2015 and 2020, we are going to select the observations for those two countries and that time range. Then we want change the data format so that the expenditure for Australia and the expenditure for Germany across different years appears in two different columns.

Fill in the blanks for the following code to get our desired output:

exp2 <- expenditure %>% 
  # (a) which pivot function
  # (b) which id_cols
  # (c) which column forms names_from
  # (d) which colum forms values_from
  dplyr::---(Entity %in% c("Australia", "Germany",
                Year >= 2015) %>%
  pivot_---(id_cols = ---, 
              names_from = ---,
              values_from = ---)

1. select

   filter

   military_expenditure

   Germany
2. longer()

   wider()

   year
3. Military_expenditure

   Time

   Year
4. Country

   Entity

   Australia