These functions convert the coded values returned from NASIS or SDA to factors (e.g. 1 = Alfisols) using the metadata tables from NASIS. For SDA the metadata is pulled from a static snapshot in the soilDB package (/data/metadata.rda).
uncode( df, invert = FALSE, db = "NASIS", droplevels = FALSE, stringsAsFactors = NULL, dsn = NULL ) code(df, db = NULL, droplevels = FALSE, stringsAsFactors = NULL, dsn = NULL)
converts the code labels back to their coded values (
label specifying the soil database the data is coming from, which indicates whether or not to query metadata from local NASIS database ("NASIS") or use soilDB-local snapshot ("LIMS" or "SDA")
logical: indicating whether to drop unused levels in classifying factors. This is useful when a class has large number of unused classes, which can waste space in tables and figures.
Optional: path to local SQLite database containing NASIS
table structure; default:
data.frame with the results.
These functions convert the coded values returned from NASIS into their plain text representation. It duplicates the functionality of the CODELABEL function found in NASIS. This function is primarily intended to be used internally by other soilDB R functions, in order to minimize the need to manually convert values.
The function works by iterating through the column names in a data frame and looking up whether they match any of the ColumnPhysicalNames found in the metadata domain tables. If matches are found then the columns coded values are converted to their corresponding factor levels. Therefore it is not advisable to reuse column names from NASIS unless the contents match the range of values and format found in NASIS. Otherwise uncode() will convert their values to NA.
When data is being imported from NASIS, the metadata tables are sourced directly from NASIS. When data is being imported from SDA or the NASIS Web Reports, the metadata is pulled from a static snapshot in the soilDB package.
options(soilDB.NASIS.skip_uncode = TRUE) to bypass decoding logic; for instance when using soilDB NASIS functions with custom NASIS snapshots that have already been decoded.
# convert column name `fraghard` (fragment hardness) codes to labels uncode(data.frame(fraghard = 1:10)) #> fraghard #> 1 noncemented #> 2 indurated #> 3 moderately cemented #> 4 strongly cemented #> 5 weakly cemented #> 6 extremely weakly #> 7 very weakly #> 8 very strongly #> 9 weakly #> 10 moderately # convert column name `fragshp` (fragment shape) labels to codes code(data.frame(fragshp = c("flat", "nonflat"))) #> fragshp #> 1 1 #> 2 2