Reshape

Coral.Reshape changes a frame between wide and long layouts:

Operation	Result
melt(frame, id_cols, value_cols)	Repeats string id columns and places float value columns into variable and value columns
pivot(frame, index_col, columns_col, values_col)	Makes one float output column per distinct string value in columns_col
stack(frame)	Calls melt with no id columns and every column as a value column
unstack(frame, index_col)	Calls pivot using variable and value

melt needs string id columns and float value columns. It emits all rows for the first value column, then all rows for the next. pivot needs string index and category columns and a float values column. A missing index/category combination produces NaN; when several input rows have the same combination, the first matching value is used.

module Coral.BookReshape
import Coral.Frame (FloatCol, StringCol, from_pairs, nrows)
import Coral.Reshape (melt)
export (main)
def main() -> i64 = {
  frame = from_pairs([("city", StringCol(["london", "paris", "oslo"])), ("qty", FloatCol(to_tensor([5.0f32, 6.0f32, 7.0f32]))), ("price", FloatCol(to_tensor([10.0f32, 20.0f32, 30.0f32])))])
  melted = melt(frame, ["city"], ["qty", "price"])
  nrows(melted)
}

main returns 6: three source rows for each of two value columns. The output column order is variable, value, then city.