R: Confront data with a (set of) expressionset(s)

confront {validate} | R Documentation

## Confront data with a (set of) expressionset(s)

### Description

An expressionset is a general class storing rich expressions (basically expressions and some meta data) which we call 'rules'. Examples of expressionset implementations are `validator` objects, storing validation rules and `indicator` objects, storing data quality indicators. The `confront` function evaluates the expressions one by one on a dataset while recording some process meta data. All results are stored in a (subclass of a) `confrontation` object.

### Usage

    confront(dat, x, ref, ...)

    ## S4 method for signature 'data.frame,indicator,ANY'
    confront(dat, x, key = NULL, ...)

    ## S4 method for signature 'data.frame,indicator,environment'
    confront(dat, x, ref, key = NULL, ...)

    ## S4 method for signature 'data.frame,indicator,data.frame'
    confront(dat, x, ref, key = NULL, ...)

    ## S4 method for signature 'data.frame,indicator,list'
    confront(dat, x, ref, key = NULL, ...)

    ## S4 method for signature 'data.frame,validator,ANY'
    confront(dat, x, key = NULL, ...)

    ## S4 method for signature 'data.frame,validator,environment'
    confront(dat, x, ref, key = NULL, ...)

    ## S4 method for signature 'data.frame,validator,data.frame'
    confront(dat, x, ref, key = NULL, ...)

    ## S4 method for signature 'data.frame,validator,list'
    confront(dat, x, ref, key = NULL, ...)

### Arguments

`dat` | An R object carrying data
`x` | An R object carrying `rule`s.
`ref` | Optionally, an R object carrying reference data. See examples for usage.
`...` | Options used at execution time (especially `'raise'`). See `voptions`.
`key` | (optional) name of identifying variable in x.

### Reference data

Reference data is typically a `list` with a items such as a code list, or a data frame of which rows match the rows of the data under scrutiny.

### See Also

`voptions`

Other confrontation-methods: `[,expressionset-method`, `as.data.frame,confrontation-method`, `confrontation-class`, `errors()`, `event()`, `keyset()`, `length,expressionset-method`, `values()`

Other validation-methods: `aggregate,validation-method`, `all,validation-method`, `any,validation-method`, `barplot,validation-method`, `check_that()`, `compare()`, `event()`, `plot,validation-method`, `sort,validation-method`, `summary()`, `validation-class`, `values()`

Other indication-methods: `event()`, `indication-class`, `summary()`

### Examples

    # a basic validation example
    v <- validator(height/weight < 0.5, mean(height) >= 0)
    cf <- confront(women, v)
    summary(cf)
    plot(cf)
    as.data.frame(cf)

    # an example checking metadata
    v <- validator(nrow(.) == 15, ncol(.) > 2)
    summary(confront(women, v))

    # An example using reference data
    v <- validator(weight == ref$weight)
    summary(confront(women, v, women))

    # Usging custom names for reference data
    v <- validator(weight == test$weight)
    summary( confront(women,v, list(test=women)) )

    # Reference data in an environment
    e <- new.env()
    e$test <- women
    v <- validator(weight == test$weight)
    summary( confront(women, v, e) )

    # the effect of using a key
    w <- women
    w$id <- letters[1:nrow(w)]
    v <- validator(weight == ref$weight)

    # with complete data; already matching
    values( confront(w, v, w, key='id'))

    # with scrambled rows in reference data (reference gets sorted according to dat)
    i <- sample(nrow(w))
    values(confront(w, v, w[i,],key='id'))

    # with incomplete reference data
    values(confront(w, v, w[1:10,],key='id'))

[Package validate version 0.9.3 Index]