expss (version 0.5.5)

modify: Modify data.frame/conditionally modify data.frame

Description

modify evaluates expression expr in the context of data.frame data. It works similar to within in base R but try to return new variables in order of their appearance in the expression. modify_if modifies only rows for which cond has TRUE. Other rows remain unchanged. Newly created variables also will have values only in rows for which cond has TRUE. There will be NA's in other rows. This function tries to mimic SPSS "DO IF(). ... END IF." statement. There is a special constant .n which equals to number of cases in data for usage in expression inside modify. Inside modify_if .n gives number of rows which will be affected by expressions. Inside these functions you can use set function which creates variables with given name/set values to existing variables - .set. It is possible with set to assign values to multiple variables at once.

Usage

modify(data, expr)
data %modify% expr
modify_if(data, cond, expr)

Arguments

data

data.frame

expr

expression(s) that should be evaluated in the context of data.frame data

cond

logical vector or expression. Expression will be evaluated in the context of the data.

Value

Both functions returns modified data.frame

Examples

dfs = data.frame(
    test = 1:5,
    aa = rep(10, 5),
    b_ = rep(20, 5),
    b_1 = rep(11, 5),
    b_2 = rep(12, 5),
    b_3 = rep(13, 5),
    b_4 = rep(14, 5),
    b_5 = rep(15, 5) 
)


# calculate sum of b* variables
modify(dfs, {
    b_total = sum_row(b_, b_1 %to% b_5)
    var_lab(b_total) = "Sum of b"
    random_numbers = runif(.n) # .n usage
})

# 'set' function
# new variables filled with NA
modify(dfs, {
    set('new_b`1:5`')
})

# 'set' function
# set values to existing/new variables
# expression in backticks will be expanded - see ?subst
modify(dfs, {
    set('new_b`1:5`', b_1 %to% b_5)
})


# conditional modification
modify_if(dfs, test %in% 2:4, {
    aa = aa + 1    
    a_b = aa + b_    
    b_total = sum_row(b_, b_1 %to% b_5)
    random_numbers = runif(.n) # .n usage
})