The main motivation for developing the libr package
is to create and use data libraries and data dictionaries. These
concepts are useful when dealing with sets of related data files. The
libname() function allows you to define a library for an
entire directory of data files. The library can then be manipulated as a
whole using the lib_* functions in the
libr package.
There are four main libr functions for creating and using a data library:
The libname() function creates a data library. The
function has parameters for the library name and a directory to
associate it with. If the directory has existing data files, those data
files will be automatically loaded into the library. Once in the
library, the data can be accessed using list syntax.
You may create a data library for several different types of files:
‘rds’, ‘Rdata’, ‘rda’, ‘csv’, ‘xlsx’, ‘xls’, ‘sas7bdat’, ‘xpt’, and
‘dbf’. The type of library is defined using the engine
parameter on the libname() function. The default data
engine is ‘rds’. The data engines will attempt to identify the correct
data type for each column of data. You may also control the data type of
the columns using the import_specs parameter and the
specs() and import_spec() functions.
If you prefer to access the data via the workspace, call the
lib_load() function on the library. This function will load
the library data into the parent frame, where it can be accessed using a
two-level (<library>.<dataset>) name.
When you are done with the data, call the lib_unload()
function to remove the data from the parent frame and put it back in the
library list. To write any added or modified data to disk, call the
lib_write() function. The lib_write() function
will only write data that has changed since the last write.
The following example will illustrate some basic functionality of the libr package regarding the creation of libnames and use of dictionaries. The example first places some sample data in a temp directory for illustration purposes. Then the example creates a libname from the temp directory, loads it into memory, adds data to it, and then unloads and writes everything to disk:
library(libr)
# Create temp directory
tmp <- tempdir()
# Save some data to temp directory
# for illustration purposes
saveRDS(trees, file.path(tmp, "trees.rds"))
saveRDS(rock, file.path(tmp, "rocks.rds"))
# Create library
libname(dat, tmp)
# library 'dat': 2 items
# - attributes: not loaded
# - path: C:\Users\User\AppData\Local\Temp\RtmpCSJ6Gc
# - items:
# Name Extension Rows Cols Size LastModified
# 1 rocks rds 48 4 3.1 Kb 2020-11-05 23:25:34
# 2 trees rds 31 3 2.4 Kb 2020-11-05 23:25:34
# Examine data dictionary for library
dictionary(dat)
# A tibble: 7 x 9
# Name Column Class Label Description Format Width Rows NAs
# <chr> <chr> <chr> <lgl> <lgl> <lgl> <lgl> <int> <int>
# 1 rocks area integer NA NA NA NA 48 0
# 2 rocks peri numeric NA NA NA NA 48 0
# 3 rocks shape numeric NA NA NA NA 48 0
# 4 rocks perm numeric NA NA NA NA 48 0
# 5 trees Girth numeric NA NA NA NA 31 0
# 6 trees Height numeric NA NA NA NA 31 0
# 7 trees Volume numeric NA NA NA NA 31 0
# Load library
lib_load(dat)
# Examine workspace
ls()
# [1] "dat" "dat.rocks" "dat.trees" "tmp"
# Use data from the library
summary(dat.rocks)
# area peri shape perm
# Min. : 1016 Min. : 308.6 Min. :0.09033 Min. : 6.30
# 1st Qu.: 5305 1st Qu.:1414.9 1st Qu.:0.16226 1st Qu.: 76.45
# Median : 7487 Median :2536.2 Median :0.19886 Median : 130.50
# Mean : 7188 Mean :2682.2 Mean :0.21811 Mean : 415.45
# 3rd Qu.: 8870 3rd Qu.:3989.5 3rd Qu.:0.26267 3rd Qu.: 777.50
# Max. :12212 Max. :4864.2 Max. :0.46413 Max. :1300.00
# Add data to the library
dat.trees_subset <- subset(dat.trees, Girth > 11)
# Add more data to the library
dat.cars <- mtcars
# Unload the library from memory
lib_unload(dat)
# Examine workspace again
ls()
# [1] "dat" "tmp"
# Write the library to disk
lib_write(dat)
# library 'dat': 4 items
# - attributes: not loaded
# - path: C:\Users\User\AppData\Local\Temp\RtmpCSJ6Gc
# - items:
# Name Extension Rows Cols Size LastModified
# 1 rocks rds 48 4 3.1 Kb 2020-11-05 23:37:45
# 2 trees rds 31 3 2.4 Kb 2020-11-05 23:37:45
# 3 cars rds 32 11 7.3 Kb 2020-11-05 23:37:45
# 4 trees_subset rds 23 3 1.8 Kb 2020-11-05 23:37:45
# Clean up
lib_delete(dat)
# Examine workspace again
ls()
# [1] "tmp"Next: Library Management