# Simple-only data (no 1:n rows)
df_simple <- tibble::tribble(
~item, ~item_code_harm, ~year, ~value, ~type,
"wheat", 1, 2000, 5, "simple",
"barley", 2, 2000, 3, "simple",
"oats", 2, 2000, 2, "simple"
)
harmonize_interpolate(df_simple)
# Mixed simple + 1:n data
df_mixed <- tibble::tribble(
~item, ~item_code_harm, ~year, ~value, ~type,
"wheatrice", 1, 2000, 20, "1:n",
"wheatrice", 2, 2000, 20, "1:n",
"wheat", 1, 2000, 8, "simple",
"rice", 2, 2000, 12, "simple"
)
harmonize_interpolate(df_mixed)
# Multiple years with share interpolation
# Shares are known in 2000 and 2002; 2001 is interpolated.
df_years <- tibble::tribble(
~item, ~item_code_harm, ~year, ~value, ~type,
"wheat", 1, 2000, 6, "simple",
"rice", 2, 2000, 4, "simple",
"wheatrice", 1, 2001, 10, "1:n",
"wheatrice", 2, 2001, 10, "1:n",
"wheat", 1, 2002, 8, "simple",
"rice", 2, 2002, 2, "simple"
)
harmonize_interpolate(df_years)
# With extra grouping columns
df_grouped <- tibble::tribble(
~item, ~item_code_harm, ~year, ~value, ~type, ~country,
"wheat", 1, 2000, 6, "simple", "usa",
"rice", 2, 2000, 4, "simple", "usa",
"wheatrice", 1, 2001, 10, "1:n", "usa",
"wheatrice", 2, 2001, 10, "1:n", "usa",
"wheat", 1, 2002, 8, "simple", "usa",
"rice", 2, 2002, 2, "simple", "usa",
"wheat", 1, 2002, 8, "simple", "germany"
)
harmonize_interpolate(df_grouped, country)
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