based on the sparse input information i suggest to use the pivoting node with Row as Group column,
Column as Pivot columns and Value (aggregation: first) in Manual Aggregation.
You are right, a bit elaboration would definitely help. An analytical instrument generates an output file where data are presented as a list of several columns. Among those outputs, there are values for a row, a column, and a derived analytical measurement. The output is generated as a list, not necessarily sorted.
To streamline data analytics, we need to generate two-dimensional matrices of data. Rows and columns of each matrix are defined as values. Therefore, we need to use these values for rows and columns as indices to generate a new two-dimensional table. Following your advice for using a pivoting node where groups columns are rows, pivots are columns, and manual aggregation indicates the measurement the result creates the desired table.