| auto_melt | R Documentation | 
When at least 3 country names or years are found in the column names, the function will automatically transform the table from a wide to a long format by pivoting the country/year columns.
This is equivalent to applying tidyr::pivot_longer() or data.table::melt() on the columns with years or countries as names.
The function is able to detect years also when they are preceded by a prefix.
auto_melt(
  x,
  names_to = "pivoted_colnames",
  values_to = "pivoted_data",
  verbose = TRUE,
  pivoting_info = FALSE
)
x | 
 A data.frame object to check and pivot country or year columns.  | 
names_to | 
 String indicating how the column holding the name of the pivoted columns should be called in the output table. Default is   | 
values_to | 
 String indicating how the column containing the values of the pivoted columns should be called in the output table. Default is   | 
verbose | 
 Logical value. If set to   | 
pivoting_info | 
 Logical value indicating whether to return the list of names of the column that have been pivoted. Default is   | 
A table transformed into a "long" format by pivoting country or year columns. If year columns are found, a numeric column called "year_pivoted_colnames" is added isolating the years extracted from the table header's.
auto_merge, find_countrycol,find_timecol
# example data
example <- data.frame(Date = c("01.01.2019", "01.02.2019", "01.03.2019"),
                      Japan = 1:3,
                      Norway = 2:4,
                      Germany = 3:5,
                      US = 4:6)
example2 <- data.frame(Sector = c("Agriculture", "Mining", "Forestry"),
                       X2000 = 1:3,
                       X2001 = 2:4,
                       X2002 = 3:5,
                       X2003 = 4:6)
# examples pivotting countries and years from column names
auto_melt(example)
auto_melt(example2)
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