Changing Class of Column Across Multiple Dataframes

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I have a list of 59 data frames that I want to merge together. Unfortunately, because I have scraped many of them, the columns in the data frames have different classes. They all have the column "Name", some in factor form and some in character form. I want to change all of them to character form. I tried the following

dts <- c("Alabama","Alaska","Arizona","Arkansas","California","Colorado","Connecticut","Delaware","Florida",
               "Georgia","Hawaii","Idaho","Illinois","Indiana","Iowa","Kansas","Kentucky","Louisiana","Maine",
               "Maryland","Massachusetts","Michigan","Minnesota","Mississippi","Missouri","Montana","Nebraska",
               "Nevada","New_Hampshire","New_Jersey","New_Mexico","New_York","North_Carolina","North_Dakota",
               "Ohio","Oklahoma","Oregon","Pennsylvania","Rhode_Island","South_Carolina","South_Dakota","Tennessee",
               "Texas","Utah","Vermont","Virginia","Washington","West_Virginia","Wisconsin","Wyoming","Federal",
               "CCJail","DC","LAJail","NOLA","NYCJail","OCJail","PhilJail","TXJail")


for(i in 1:length(dts)){
        dts[i]$Name <- as.character(dts[i]$Name)
}

but it only gave me the error "Error: $ operator is invalid for atomic vectors". Does anyone know of a good work-around? Thanks in advance for the help!

My ultimate goal is to run

dta <-dplyr::bind_rows(Alabama,Alaska,Arizona,Arkansas,California,Colorado,Connecticut,Delaware,Florida,
       Georgia,Hawaii,Idaho,Illinois,Indiana,Iowa,Kansas,Kentucky,Louisiana,Maine,
       Maryland,Massachusetts,Michigan,Minnesota,Mississippi,Missouri,Montana,Nebraska,
       Nevada,New_Hampshire,New_Jersey,New_Mexico,New_York,North_Carolina,North_Dakota,
       Ohio,Oklahoma,Oregon,Pennsylvania,Rhode_Island,South_Carolina,South_Dakota,Tennessee,
       Texas,Utah,Vermont,Virginia,Washington,West_Virginia,Wisconsin,Wyoming,Federal,CCJail,
       DC,LAJail,NOLA,NYCJail,OCJail,PhilJail,TXJail)

But I get the error "Error: Can't combine ..1$Residents.Confirmed and ..2$Residents.Confirmed ." There are a ton of columns in each data frame, and they are different classes very often. if anyone has a more elegant solution, I would also be open to that instead! Thanks!

dplyr dataframe r
3 Answers

We can get the datasets loaded into a list with mget (assuming the dataset objects are already created in the global environment) and then loop over the list with map, change the class of 'Name' column in mutate and row bind with suffix _dfr in map

library(dplyr)
library(purrr)
out <- map_dfr(mget(dts), ~ .x %>% 
                  mutate(Name = as.character(Name)))

If there are many columns that are different class. May be, it is better to convert to a single class for all the columns and then bind

out <- map_dfr(mget(dts), ~ .x %>%
                   mutate(across(everything(), as.character)))
out <- type.convert(out, as.is = TRUE)

If the dplyr version is < 1.0.0, use mutate_all

out <- map_dfr(mget(dts), ~ .x %>%
               mutate_all(as.character))
user_37322710 
d1 <- data.frame(
  Name = as.factor(c("name1", "name2")),
  Residents.Confirmed = c(0,1)
  )
d2 <- data.frame(
  Name = c("name3", "name4"),
  Residents.Confirmed = c(2,3)
)
dataframes_list <- list(d1, d2)
for(i in 1:length(dataframes_list)){
  dataframes_list[[i]]$Name <- as.character(dataframes_list[[i]]$Name)
}
bind_rows(dataframes_list)
user_112975960

Base R solution:

type.convert(do.call("rbind", 
        Map(function(x){data.frame(lapply(x, as.character))}, dataframes_list)))

Data thanks @chase171:

d1 <- data.frame(
  Name = as.factor(c("name1", "name2")),
  Residents.Confirmed = c(0,1)
)
d2 <- data.frame(
  Name = c("name3", "name4"),
  Residents.Confirmed = c(2,3)
)
dataframes_list <- list(d1, d2)
user_92031580
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