R: Identify and corrects variable formats

format_corrector | R Documentation

## Identify and corrects variable formats

### Description

The function creates a loop to compare for each variable the values it have with the usual ones that typical R formats have in order to correct, for example, missing value or dates stored as a character. It also specify for each variable the most appropriate SPSS format that it should have.

### Usage

    format_corrector(table,identif=NULL,force=FALSE,rate.miss.date=0.5)

### Arguments

`table` | The data set we want to correct.
`identif` | The name of the identification variable included in the data frame. It will be used to list the individuals who had any problems during the execution of the function.
`force` | If TRUE, run format_corrector even if "fixed.formats" attribute is TRUE
`rate.miss.date` | The maximum rate of missing date fields we want the function to accept.The function details which fields have been lost anyways.

### Details

If the date variable don't have chron format it must be in one of the following formats, else the function leaves it as a character:
—-dates separator must be one of the following:("-","/",".").
—-hour separator must be ":".

### Value

A single data frame which results from the function.

### Note

This function may not be completely optimal so it might have problems when correcting huge data frames.

### See Also

`SPSS_export`

### Examples

    a<-c(1,NA,3,5,".")
    b<-c("19/11/2006","05/10/2011","09/02/1906","22/01/1956","10/10/2010")
    c<-101:105
    x<-data.frame(a,b,c)
    sapply(x,class)
    x_corr<-format_corrector(x)
    sapply(x_corr,class)