... variables.^2.1

But use this cautiously because size-distribution variables are special and sometimes cause problems when manipulating the resulting data.frame. This is discussed later in association with “tibbles.”

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

... variable).^3.1

Subsetting will often lose some attributes so special steps are needed to preserve them if that is desired.

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

... lost.^4.1

Preserving attributes is desirable because the attributes are often used by Ranadu routines. The bin assignments for size distributions are carried in an attribute, as is the data rate (used in spectral analysis). Variables with the same “short_name” attributes are redundant measurements of the same quantity, so it is often useful to plot all with matching short_names together. RANADU plot routines use a “label” attribute for default axes titles. Finally, the function makeNetCDF( ) makes a new netCDF file with the variables and attributes in the data.frame, and it requires some attributes (like the “Dimension” attribute) or it will fail.

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

... example.^4.2

The matrix layout can also be used to display plots in multiple columns or in multiple rows and columns.

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

... plots.^4.3

“suppressWarnings” is used here because otherwise the routine prints a warning message about mismatches among variable attributes.

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.

... Ranadu::plotSD().^6.1

df2tibble() will also convert back to normal Ranadu structure with the argument “reverse = TRUE”.

.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.
.