The function `check_data()` serves the purpose of performing a preliminary check and fix some evident issues. However, the function cannot resolve all data quality-related problems.
Arguments
- data
A data frame or data table.
- max_levels
An integer specifying the maximum number of levels allowed for a factor variable. This is used to detect potential ID columns that are often non-informative for imputation. Default: 50% of the number of rows, rounded to the nearest integer.
- verbose
Verbose setting. If
TRUE, will print out warnings when data issues are found. Default:TRUE.
Examples
bad_data <- data.frame(Amount = c(Inf, 10, 201.5), Type = factor(c("NaN", "B", "A")))
checked_data <- check_data(data = bad_data, verbose = TRUE)
#>
#> ── Sanity checks begins ────────────────────────────────────────────────────────
#> ! Character "NaN" values detected in `Type`. They have been converted to NA.
#> ! Numeric Inf/-Inf values detected in `Amount`.They have been converted to NA.
#> ✔ All sanity checks completed.