Use first digit as factor to standardize values in R - r

Question

I have large data frame tocalculate from a survey (original data frame brfss2013 where one of the variables represents the number of times a person checks blood glucose levels. The data is in 3 digits:
First digit tells you if the measurements are per day (1), per week (2), per month (3)or per year (4). The second and third digits represent the actual value.
Example: 101 is once ( _01) per day (1 _ _), 202 is twice per week, etc.
I want to standardize everything to get value of times per year. So I will multiply the 2nd and 3rd digits by 365, 52.143, 12 and 1 (days, weeks, months, year).
I think I would be able to "select" the digits to use, but I'm not sure how to write something that can work with different rows with different set of instructions.
EDIT:
Adding my attempt and sample data.
tocalculate <- brfss2013 %>%
filter(nchar(bldsugar) > 2)
bldsugar2 <- sapply(tocalculate$bldsugar, function(x) {
if (substr(x,1,1) == 1) {x*365}
if (substr(x,1,1) == 2) {x*52}
if (substr(x,1,1) == 3) {x*12}
if (substr(x,1,1) == 4) {x*365}
})
I'm getting a lot of NULL values though...

Answer 1

Since you're already using dplyr, recode is a handy function. I use %/% to see how many times 100 goes in to each bldsugar value and %% to get the remainder when divided by 100.
# sample data
brfss_sample = data.frame(bldsugar = c(101, 102, 201, 202, 301, 302, 401, 402))
library(dplyr)
mutate(
brfss_sample,
mult = recode(
bldsugar %/% 100,
`1` = 365.25,
`2` = 52.143,
`3` = 12,
`4` = 1
),
checks_per_year = bldsugar %% 100 * mult
)
# bldsugar mult checks_per_year
# 1 101 365.250 365.250
# 2 102 365.250 730.500
# 3 201 52.143 52.143
# 4 202 52.143 104.286
# 5 301 12.000 12.000
# 6 302 12.000 24.000
# 7 401 1.000 1.000
# 8 402 1.000 2.000
You could, of course, remove the mult column (or combine the definitions so it is never created in the first place).

Answer 2

#Data
set.seed(42)
x = sample(101:499, 100, replace = TRUE)
#1st digit
as.factor(floor((x/100)))
#Values
((x/100) %% 1) * 100

Answer 3

Perhaps the first thing you can do is to split the 3-digit variable into two variables. The first variable is only one digit, which shows sampling frequency; and the second variable shows times of measurement.
In R, substr or substring can select the string by specifying the first and last position to subset.
# Create example data frame
ex_data <- data.frame(var = c("101", "202", "204"))
# Split the variable to create two new columns
ex_data$var1 <- substring(ex_data$var, first = 1, last = 1)
ex_data$var2 <- substring(ex_data$var, first = 2, last = 3)
# Remove the original variable
ex_data$var <- NULL
After this, you can manipulate your data frame. Perhaps convert var1 to factor and var2 to numeric for further manipulation and analysis.