Data columns can have a variety of attributes associated with them. Your script might need to specify these attributes if it's creating new data columns, or it might need to change the attributes of an existing data column. Column attributes include things like the type of data, the modeling type, the format for numeric data, the current values in the column either as literal values or as a formula, and a pre-selected analysis role. You can specify column attributes as named arguments for the New Column message to the data table, or you can send them as individual messages to an existing data column. One column attribute is the format of numeric data, and there are a lot of formats available. Formats don't change the values that are stored in the data column, they simply change how the data appear in the data column and in analysis platforms. For example, suppose you have a data table with measurement values that include decimal places. You can apply the fixed decimal format to display the values with a specified number of decimal places--the stored value is unchanged, but the value that you see is rounded. Recall that dates are stored in a data table as the number of seconds since midnight January first, You can apply one of the date and time formats to display dates in a more recognizable form, like a month/day/year and time. Again, this does not change the stored data. Some attributes can be turned on or off using Boolean values. Examples include using the column values as a label, locking the column from scrolling horizontally, hiding the column in the data table, excluding the column from analysis roles, or locking the data column so that it can't be edited. Like the other attributes, these can be arguments to the New Column message, or sent as messages to an existing column.
