This menu is only active when a table is selected.
Selecting the Set Column As item opens a sub-menu of command that are used to define the kind of data stored in the various columns of a table.
Define the selected column as abscissa for the plots. You can define more than one column as X-values in a table, they are referenced as X1, X2, etc.
For 2D plots, this command defines the selected column as Y-values for the plots. For 3D plots, Y columns can be used as the second abscissa.
For 3D plots, Z columns will be used as plotted values.
Define the selected column for use as the error bar width for the abscissae.
Define the selected column for use as the error bar heights for the Y-values.
Set the selected columns as read-only.
Restore write access to the selected columns.
Sets the selected columns as label columns. Can be used for comments and row descriptions.
No special function is assigned. The selected column can be used in different ways in several plots (as X values, Y values, etc). These columns are disregarded in statistical calculations.
This command is used to define the global parameters of each column such as numeric format, column name, etc. See the corresponding dialog box section for more details.
This command is used to fill the selected column with the values resulting from a mathematical formula. See the corresponding dialog box section for more details.
When you fill a column (named for example 'C1') with the results of a formula (by using the Set Column Values... command), the values of the column are calculated only once when you define the formula. If your formula depends on values of another column (name for example 'C2'), the values of 'C1' are not updated if you modify the values in 'C2'. This command is used to recalculate the values of the selected column.
These commands are used to fill selected columns with special values:
Each element in the column is filled with its corresponding row number.
Each element in the column is filled with a random value between 0 and 1.
The rows in the selected column are filled with normally distributed random values calculate using the Ziggurat method with a mean of 0.0 and a standard deviation of 1.0. The computational routine is from the Gnu Scientific Library (look here for more details).
Removes all the values of the selected column.
Adds a new column to the table. Regardless the selected column, new columns are inserted to the right of the rightmost column in the table.
Used to define the number of columns in the table. Columns are added/removed from the right hand side of the table. Be Careful! If you decrease the number of columns in a table, any data contained in the removed columns will be lost!
The Hide Selected Columns command hides all the selected columns. The remaining visible columns are grouped together into a single block. Hidden columns may be shown using the Show All Columns command.
The Show All Columns command unhides any hidden columns in the selected table.
The Set Optimal Column Width command resets the width of all selected columns to a value that is optimal for the data that is contained in the column. Optimal width is considered to be just wide enough to show all digits.
Moves the selected column to the beginning of the table.
Moves the selected column to the left.
Moves the selected column to the right.
Moves the selected column to the end of the table.
Swaps the selected columns.
Allows direct definition of the number of rows in the table. Rows are added/removed from the end of the table. Be Careful! If you decrease the number of rows in a table, any data contained in removed rows will be lost.
A dialog is opened that permits selection, and subsequent deletion, of a range of rows selected by row index number.
These commands are used to move selected rows up or down in a table:
The selected row is moved up one place in the table.
The selected row is moved down one place in the table.
This command opens a dialog which allows you to select the row index that will become the current row in the selected table or matrix.
This command opens a dialog which allows you to select the column index that will become the current column in the selected table or matrix.
The Extract Data... command opens a dialog which allows you to define a set of conditions that are used to filter the data in the currently active table. When a condition has been defined, Applying the condition will create a new table into which all rows that meet the condition will be copied. The original table is unchanged. For example, the condition col("1") > 0.5 will generate a new table that contains all the rows from the active table which have a value greater than 0.5 in column 1. See the corresponding dialog box section for more details.
The commands in this submenu may be used to convert a table into a matrix. Their main utility might be to import data from files into matrices: first import the data into a table and then use these commands to convert the table into a matrix.
This command creates a new matrix having the same dimensions (rows/columns) as the input table. Each cell in the table has its corresponding cell in the resulting matrix. There are no special requirements on the data values in the table to be converted.
This command bins XY data, meaning that it creates a frequency count of the data points falling within a given XY range and stores the bin counts as Z values in a new matrix. It opens the the Bin Matrix Dialog that allows to customize the new matrix in terms of dimensions and coordinates. The input data must be a single Y column that has a X column associated to it.
This command creates a new matrix from a a table that contains regularly spaced XY data. In order for the input data to be classified as regular, the values in the X and Y columns must meet specific requirements: each X value must have the same number of Y values and each Y value must have the same number of X values. In addition, both the X and the Y data values must be equally spaced: only small irregularities of the data are allowed (15% tolerance).
Opens the the Random XYZ Gridding dialog that allows to customize the process of generating a new matrix from a collection of randomly distributed XYZ data samples, using Shepard's method. The input data must be a single Z column that has a X and a Y column associated to it.