Data manipulation.

This is a series of functions designed for a fast coding of replacements both, as internal functions and in workflows dealing with information stored in vectors. Such functions are especially useful when handling with functional traits stored in taxlist objects.

replace_x() is used to exchange values in vectors. replace_idx() changes values in vectors by matching indices or conditions. The function replace_na() works in the same way as replace_idx() but will only insert values in empty elements (NAs).

Usage

replace_x(x, old, new)

replace_idx(x, idx1 = x, idx2 = idx1, new)

replace_na(x, idx1, idx2 = idx1, new)

Arguments

x

A vector to be modified. In the case of insert_rows(), x is a data frame.

old

A vector with values to be replaced by replace_x() in a vector.

new

A vector containing values to be inserted, either comparing values or using indices.

idx1, idx2

Indices applied for value replacements to match x with new, respectively. If idx2 is not provided, it will be assumed as equivalent to idx1.

Value

A vector or data frame with the modified values.

Author

Miguel Alvarez.

Examples

## Replace values in vector
replace_x(x = letters, old = c("b", "p", "f"), new = c("bee", "pork", "fungus"))
#>  [1] "a"      "bee"    "c"      "d"      "e"      "fungus" "g"      "h"     
#>  [9] "i"      "j"      "k"      "l"      "m"      "n"      "o"      "pork"  
#> [17] "q"      "r"      "s"      "t"      "u"      "v"      "w"      "x"     
#> [25] "y"      "z"     

## Replace values using indices
replace_idx(x = letters, idx1 = 1:length(letters), idx2 = c(2, 7, 17),
  new = c("second", "seventh", "seventeenth"))
#>  [1] "a"           "second"      "c"           "d"           "e"          
#>  [6] "f"           "seventh"     "h"           "i"           "j"          
#> [11] "k"           "l"           "m"           "n"           "o"          
#> [16] "p"           "seventeenth" "r"           "s"           "t"          
#> [21] "u"           "v"           "w"           "x"           "y"          
#> [26] "z"          

## Replace values if they are NAs
letters[2] <- NA
replace_na(x = letters, idx1 = 1:length(letters), idx2 = c(1:3),
  new = c("alpha", "beta", "zeta"))
#>  [1] "a"    "beta" "c"    "d"    "e"    "f"    "g"    "h"    "i"    "j"   
#> [11] "k"    "l"    "m"    "n"    "o"    "p"    "q"    "r"    "s"    "t"   
#> [21] "u"    "v"    "w"    "x"    "y"    "z"   

## The same applications but this time for functional traits
summary(as.factor(Easplist$life_form))
#>   acropleustophyte        chamaephyte     climbing_plant facultative_annual 
#>                  8                 25                 25                 20 
#>    obligate_annual       phanerophyte   pleustohelophyte         reed_plant 
#>                114                 26                  8                 14 
#>      reptant_plant      tussock_plant               NA's 
#>                 19                 52               3576 

# Merge annuals
Easplist@taxonTraits$lifeform <- replace_x(x = Easplist@taxonTraits$life_form,
  old = c("obligate_annual", "facultative_annual"), new = c("annual", "annual"))
summary(as.factor(Easplist$lifeform))
#> acropleustophyte           annual      chamaephyte   climbing_plant 
#>                8              134               25               25 
#>     phanerophyte pleustohelophyte       reed_plant    reptant_plant 
#>               26                8               14               19 
#>    tussock_plant             NA's 
#>               52             3576 

# The same effect
Easplist@taxonTraits$lifeform <- replace_idx(x = Easplist@taxonTraits$life_form,
  idx1 = grepl("annual", Easplist@taxonTraits$life_form), idx2 = TRUE,
  new = "annual")
summary(as.factor(Easplist$lifeform))
#> acropleustophyte           annual      chamaephyte   climbing_plant 
#>                8              134               25               25 
#>     phanerophyte pleustohelophyte       reed_plant    reptant_plant 
#>               26                8               14               19 
#>    tussock_plant             NA's 
#>               52             3576