I have the following data frame in R. I would like to get fips from this dataset. I tried to use fips function in usmap (https://rdrr.io/cran/usmap/man/fips.html). But I could not get fips from this function because I need to enclose double quote. Then, I tried to use paste0(""", df$state, """), but I could not get it. Is there any efficient ways to get fips?
> df1
state county
1 california napa
2 florida palm beach
3 florida collier
4 florida duval
UPDATE
I can get "\"california\"" by using dQuote. Thanks. After the conversion of each column, I tried the followings. How do I deal with this issue?
> df1$state <- dQuote(df1$state, FALSE)
> df1$county <- dQuote(df1$county, FALSE)
> fips(state = df1$state, county = df1$county)
Error in fips(state = df1$state, county = df1$county) :
`county` parameter cannot be used with multiple states.
> fips(state = df1$state[1], county = df1$county[1])
Error in fips(state = df1$state[1], county = df1$county[1]) :
"napa" is not a valid county in "california".
> fips(state = "california", county = "napa")
[1] "06055"
We can split the dataset by state and apply the fips
library(usmap)
lapply(split(df1, df1$state), function(x)
fips(state = x$state[1], county = x$county))
#$california
#[1] "06055"
#$florida
#[1] "12099" "12021" "12031"
Or with Map
lst1 <- split(df1$county, df1$state)
Map(fips, lst1, state = names(lst1))
#$california
#[1] "06055"
#$florida
#[1] "12099" "12021" "12031"
Or with tidyverse
library(dplyr)
library(tidyr)
df1 %>%
group_by(state) %>%
summarise(new = list(fips(state = first(state), county = county))) %>%
unnest(c(new))
# A tibble: 4 x 2
# state new
# <chr> <chr>
#1 california 06055
#2 florida 12099
#3 florida 12021
#4 florida 12031
df1 <- structure(list(state = c("california", "florida", "florida",
"florida"), county = c("napa", "palm beach", "collier", "duval"
)), class = "data.frame", row.names = c("1", "2", "3", "4"))