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Include all columns of a dataframe.

All.Rd

This constructs a formula object for all the columns of a dataframe.

Usage

All(df, numeric=TRUE, character=FALSE, logical=FALSE, factor=FALSE, 
        complex=FALSE, raw=FALSE, other=FALSE,
        texify=getOption("tables.texify", FALSE))

Arguments

df

The dataframe in which to find the columns.

numeric, character, logical, factor, complex, raw

Whether to include columns of specified types. See the Details below.

other

Whether to include columns that match none of the previous types.

texify

Whether to escape LaTeX special characters in column names.

Details

This function constructs a formula from the columns of a dataframe. By default, only numeric columns are included. The arguments numeric, character, logical, factor, complex and raw control the inclusion of columns of the corresponding types. The argument other controls inclusion of any other columns.

If these arguments are TRUE, such columns will be included in the formula.

If a function (or the name of a function given as a character string) is passed, such columns will be transformed by the function before inclusion. For example, All(df, factor=as.character) will convert all factor columns into their character representation for inclusion.

In other cases, the columns will be skipped.

Value

Language to insert into the table formula to achieve the desired table.

Examples

# Show mean and sd of all numeric columns in the iris data
tabular( Species  ~ 
       All(iris)*(mean + sd), data=iris )
#>                                                                       
#>             Sepal.Length        Sepal.Width        Petal.Length       
#>  Species    mean         sd     mean        sd     mean         sd    
#>  setosa     5.006        0.3525 3.428       0.3791 1.462        0.1737
#>  versicolor 5.936        0.5162 2.770       0.3138 4.260        0.4699
#>  virginica  6.588        0.6359 2.974       0.3225 5.552        0.5519
#>                    
#>  Petal.Width       
#>  mean        sd    
#>  0.246       0.1054
#>  1.326       0.1978
#>  2.026       0.2747