NEWS.md
dataset, febr, febr2spdf, febr2xlsx, standard, header.readIndex() for reading the TXT file listing all data sets published in the FEBR.morphology: deals with depth data between parenthesis when retrieving soil color data.morphology: deal with varying number of soil color records (1 or 2)morphology: retrieve soil color data when accents are missing (“umido” or “umida”)febr2sse: updates nomenclature (SmartSolos Expert and sse); process soil consistency datamorphology: retrieve soil consistency datareadFEBR().dictionary()
standard()
table has two new valid values: metadado and versionamento.taxonomy(). Extract and process soil taxonomic data from textual soil classification description. A vignette accompanies the new function.observation(). Corrects an issue in argument checking.morphology to extract and process soil morphological properties from field soil morphology descriptions.febr2smartsolos for the following soil variables: taxonomic classification, soil matrix color (wet and dry), soil structure.febr2smartsolos() and smartsolos2febr() for soil profile data conversion between FEBR and SMARTSolos.readFEBR(): improves output object.readFEBR(): new general purpose function to download raw data.febr.repo allows user to set where the data should be read from: the remote web server or a local directoryheader() is now deprecated due to the new file structure used in FEBR. Users can now rely on the already existing metadata() to get the same resultsfebr2spdf() is now defunct.febr2sf is available as a replacement for febr2sp – sp is not dependencies anymore;febr2xlsx is now deprecated – xlsx is not dependencies anymore;layer: standard variables are only set to type character when stack = TRUE.Sys.sleep(time = 10) to pass checks in functions examples. This is necessary because the new Google Sheets API has a limit of 500 requests per 100 seconds per project, and 100 requests per 100 seconds per user (https://developers.google.com/sheets/api/limits). This issue has also been found elsewhere, e.g. https://stackoverflow.com/questions/53765222/python-google-sheets-api-limit-429-error-with-loop. We soon will remove the dependency upon googlesheets4 and thus solve this issue.febr2sf as a replacement for febr2sp;.readGoogleSheets;febr2xlsx is now deprecated and febr does not depend upon xlsx anymore;layer: standard variables are only set to type character when stack = TRUE;.readGoogleSheets;metadata: get correct file id.dataset, observacao, camada or metadado) is explicitly specified withing download functions. The user should not have to worry about this change.missing = list(coord = 'drop') in function observation() now correctly drops observations missing spatial coordinates. Thanks to Edberto Moura Lima, from the Federal University of Santa Maria, who identified the bug. Equivalent modifications were implemented in function layer().observatio(): checking if the number of observations with date is greater than the number of observations without date.unit(): checking if the value passed to an argument is valid.#VALUE! now is considered as NA. This can be found when a calculation is performed in one of the Google Sheets.tr now is considered as NA. This is frequently found in the camada table.camada_id, which is automatically set to NA_character_. In these cases, when merging repeated layer data using layer(standardization = list(repetition = "combine")), the entire observation would be merged. This was because for all layers camada_id = NA_character_, that is, camada_id was duplicated. Now duplicates are checked using duplicated(incomparables = NA) to avoid incorrect merges./. The depth data of these layes may include a plus sign indicating that the same material can be found deeper in the soil. This poses a difficulty when processing the plus sign with eval() and parse() because / is interpreted as a division sign. Now the presence of / is checked before deciding how to deal with the plus sign.- is used as a surrogate measurement unit for variables that are unitless.- is used as a surrogate measurement unit for variables that are unitless. This is necessary to perform data standardization.layer and observation when downloading a single dataset with stack = TRUE.camada_numero now is camada_id.amostra_codigo now is amostra_id.camada and observacao.camada and observacao. Now using #metadado> – as a replacement of #unidade. This allows setting multiple lines with comments.layer and observation: the measurement unit, field_unit, and true variable name, field_name, are exported as attributes of the output data.frame object.