Process a data file using metadata and codes dictionary

process_data_file() reads a data file, applies the provided metadata and codes dictionary, and organizes the data into a tidy format. The column names are determined based on the metadata scenario (e.g., "single", "single_multiple", "single_multiple_single").

Usage

process_data_file(file, metadata, dict = NULL)

Arguments

file: (String) The path to the data file
metadata: A list containing the scenario and variable information obtained from the metadata file using process_metadata_file.
dict: (Optional) A data frame containing codes dictionary information

Value

A tibble containing the processed data in a tidy format

Details

process_data_file() processes the data file according to the metadata scenario. It handles cases where variables have multiple occurrences and organizes the data into a tidy format with appropriate column names. The function relies on the read_data_file function for the actual data reading.

Examples

# \donttest{

  path <- tempfile("fcadata")
  dir.create(path)

  download_data(
    year = 2025,
    month = "September",
    dest = path
  )
#> Files successfully downloaded into /tmp/Rtmp0rXpkR/fcadata181412c6914c

  process_data_file(
    file = file.path(path, "RCB_Q202509_G20251112.TXT"),
    metadata = process_metadata_file(file.path(path, "D_RCB.TXT")),
    dict = RCB__INV_CODE
  )
#> # A tibble: 2,240 × 11
#>    SYSTEM  DIST ASSOC MONTH  YEAR UNINUM INV_CODE BKVAL MKTVAL BKVALFORSALE
#>     <int> <int> <int> <int> <int>  <int>    <int> <int>  <int>        <int>
#>  1      6    10     0     9  2025 610000       10     0      0       770093
#>  2      6    10     0     9  2025 610000       15     0      0       154555
#>  3      6    10     0     9  2025 610000       17     0      0         1917
#>  4      6    10     0     9  2025 610000       25     0      0            0
#>  5      6    10     0     9  2025 610000       29     0      0            0
#>  6      6    10     0     9  2025 610000       35     0      0            0
#>  7      6    10     0     9  2025 610000       40     0      0       284976
#>  8      6    10     0     9  2025 610000       41     0      0       400000
#>  9      6    10     0     9  2025 610000       50     0      0       250000
#> 10      6    10     0     9  2025 610000       51     0      0            0
#> # ℹ 2,230 more rows
#> # ℹ 1 more variable: MKTVALFORSALE <int>

# }