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Generate the Skeleton of a Column Key for Only New Data Files

Source: R/expand_key.R
expand_key.Rd

Data discovery–and harmonization–is an iterative process. For those already depending upon a column key and the harmonize function, it can be cumbersome to add rows to an existing column key. This function formats rows for an existing column key for only datasets that are not already (A) in the column key or (B) in the harmonized data table.

Usage

expand_key(
  key = NULL,
  raw_folder = NULL,
  harmonized_df = NULL,
  data_format = c("csv", "txt", "xls", "xlsx"),
  guess_tidy = FALSE
)

Arguments

key

(dataframe) key object including a "source", "raw_name" and "tidy_name" column. Additional columns are allowed but ignored

raw_folder

(character) folder / folder path containing data files to include in key

harmonized_df

(dataframe) harmonized data table produced with the current version of the column key. Must include a "source" column but other columns are ignored.

data_format

(character) file extensions to identify within the raw_folder. Default behavior is to search for all supported file types.

guess_tidy

(logical) whether to attempt to "guess" what the tidy name equivalent should be for each raw column name. This is accomplished via coercion to lowercase and removal of special character/repeated characters. If FALSE (the default) the "tidy_name" column is returned empty

Value

(dataframe) skeleton of rows to add to column key for data sources not already in harmonized data table

Examples

# Generate two simple tables
## Dataframe 1
df1 <- data.frame("xx" = c(1:3),
                  "unwanted" = c("not", "needed", "column"),
                  "yy" = letters[1:3])
## Dataframe 2
df2 <- data.frame("LETTERS" = letters[4:7],
                  "NUMBERS" = c(4:7),
                  "BONUS" = c("plantae", "animalia", "fungi", "protista"))

# Generate a local folder for exporting
temp_folder <- tempdir()

# Export both files to that folder
utils::write.csv(x = df1, file = file.path(temp_folder, "df1.csv"), row.names = FALSE)
utils::write.csv(x = df2, file = file.path(temp_folder, "df2.csv"), row.names = FALSE)

# Generate a column key with "guesses" at tidy column names
key1 <- ltertools::begin_key(raw_folder = temp_folder, data_format = "csv", guess_tidy = TRUE)

# Harmonize the data
harmony <- ltertools::harmonize(key = key1, raw_folder = temp_folder)

# Make a new data file
df3 <- data.frame("xx" = c(10:15),
                  "letters" = letters[10:15])

# Export this locally to the temp folder too
utils::write.csv(x = df3, file = file.path(temp_folder, "df3.csv"), row.names = FALSE)

# Identify what needs to be added to the existing column key
ltertools::expand_key(key = key1, raw_folder = temp_folder, harmonized_df = harmony,
                      data_format = "csv", guess_tidy = TRUE)
#>    source raw_name tidy_name
#> 1 df3.csv       xx        xx
#> 2 df3.csv  letters   letters