panel

panel(row, col, metrics, [rowLabel], [colLabel], [parallel=false])

row is a vector. Each element corresponds to a row in a matrix in the result.

col is a vector. Each element corresponds to a column in a matrix in the result.

metrics is one or multiple vectors. Each vector in metrics corresponds to a matrix in the result.

rowLabel is a vector of row labels for the matrix (or matrices) in the result. It is composed of distinct values in ascending order. The result only includes the rows specified in rowLabel.

colLabel is a vector of column labels for the matrix (or matrices) in the result. It is composed of distinct values in ascending order. The result only includes the columns specified in colLabel.

parallel is a Boolean value indicating whether to conduct parallel computing. The default value is false.

Rearrange metrics as a matrix (or multiple matrices). For each vector in metrics, return a matrix.

Function panel is similar to SQL pivotBy clause in that they can both rearrange data as a matrix based on 2 dimensions. The difference is that exec... pivot by... can only convert one column into a matrix whereas function panel can convert one or multiple columns into one or multiple matrices.

t = table(1 1 2 2 2 3 3 as id, 2020.09.01 + 1 3 1 2 3 2 3 as date, 1..7 as value);
// output
t;

panel(t.date, t.id, t.value);

panel(t.date, t.id, t.value, 2020.09.02 2020.09.03, 1 2);

panel(t.date, t.id, [t.value, t.value>0], 2020.09.02 2020.09.03, 1 2);

Calculate the cumulative maximum price of each stock from the matrix generated by function panel.

syms = "sym"+string(1..2)
dates = 2021.12.07..2021.12.11
t = table(loop(take{, size(syms)}, dates).flatten() as trade_date,  take(syms, size(syms)*size(dates)) as code, rand(1000, (size(syms)*size(dates))) as volume)
volume = panel(t.trade_date, t.code, t.volume, dates)
cummax(volume)