CODEWITHSUNDEEP
rdplyrtype-conversionrlangtidyeval
andrewH
andrewH

Reputation: 2321

R: Conditional evaluation of expressions given as strings as values for a dplyr mutate

I am trying to do a dplyr::mutate() using case_when to select between various formulas that are assembled from pieces that are strings. However I am clearly not converting the string properly into an expression before quoting and subsequently unquoting them. I have tried seven or eight ways of doing this, all unsuccessful.

The reason for assembling the expression from strings is that I have a large number of groups of variables that have names differing only by a suffix, for example, to distinguish variables in nominal or inflation-adjusted dollars. I use case_when because similar variables have different names, and sometimes different aggregation structures, in different years.

This is a much-simplified example:

bus_inc <- function(tb, suffix) {
  bus1     <- quo(paste0("incbus", suffix, " + ",  "incfarm", suffix, collapse = ""))
  bus2     <- quo(paste0("incbus2", suffix, " + ",  "incfarm", suffix, collapse = ""))
  bus3     <- quo(paste0("incbus", suffix, " + ",  "incfarm2", suffix, collapse = ""))
  out      <- mutate(tb, bus = case_when((year < 1968) ~ UQ(bus1),
                                   ((year > 1967) & (year < 1976)) ~ UQ(bus2),
                                   (year > 1975) ~ UQ(bus3)))
  out
}

Data:

incbus_99     <-   1:56
incfarm_99   <-  57:112
incbus2_99   <-  incbus_99 + 0.5
incfarm2_99 <-  incfarm_99 * 10
year <- 1962:2017
test_tb <- tibble(year, incbus_99, incfarm_99, incbus2_99, incfarm2_99)

my_test <- bus_inc(tb  = test_tb, suffix = "_99")
my_test

The value of bus should be 58 in year 1962 and 70.5 in 1968.

I have found a number of places that suggest parse(text="my_string") as a way of converting a string into an expression, such as this early example (2002) from Martin Maechler. But I have also found a bunch of places that say never to do this, such as Fortune 106 and this recent example from Martin Maechler. I take this forceful repudiation by the formidable Dr. Maechler of a solution he had preciously offered as strong evidence that this is not a good idea, but I do not understand his proposed alternatives, as they seem to evaluate to strings.

Upvotes: 2

Views: 209

Answers (1)

CJ Yetman
CJ Yetman

Reputation: 8848

maybe use a combination of sym() and expr() (you also need to use as.numeric because inconsistent types will throw an error in case_when)...

bus_inc <- function(tb, suffix) {
  bus1 <- expr(!!sym(paste0('incbus', suffix)) + !!sym(paste0('incfarm', suffix)))
  bus2 <- expr(!!sym(paste0('incbus2', suffix)) + !!sym(paste0('incfarm', suffix)))
  bus3 <- expr(!!sym(paste0('incbus', suffix)) + !!sym(paste0('incfarm2', suffix)))
  mutate(tb, bus = case_when(year < 1968 ~ as.numeric(!!bus1),
                             year > 1967 & year < 1976 ~ as.numeric(!!bus2),
                             year > 1975 ~ as.numeric(!!bus3)))
}

library(dplyr)

incbus_99     <-   1:56
incfarm_99   <-  57:112
incbus2_99   <-  incbus_99 + 0.5
incfarm2_99 <-  incfarm_99 * 10
year <- 1962:2017
test_tb <- tibble(year, incbus_99, incfarm_99, incbus2_99, incfarm2_99)

bus_inc(tb  = test_tb, suffix = "_99")

# # A tibble: 56 x 6
#     year incbus_99 incfarm_99 incbus2_99 incfarm2_99   bus
#    <int>     <int>      <int>      <dbl>       <dbl> <dbl>
#  1  1962         1         57        1.5         570  58  
#  2  1963         2         58        2.5         580  60  
#  3  1964         3         59        3.5         590  62  
#  4  1965         4         60        4.5         600  64  
#  5  1966         5         61        5.5         610  66  
#  6  1967         6         62        6.5         620  68  
#  7  1968         7         63        7.5         630  70.5
#  8  1969         8         64        8.5         640  72.5
#  9  1970         9         65        9.5         650  74.5
# 10  1971        10         66       10.5         660  76.5
# # ... with 46 more rows

Upvotes: 1

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