Convert data frame column values into multiple yaml file

I have a data frame which is similar to:

df <- data.frame(State = c("A", "B"),
                 Cust_Age = c(25, 50),
                 City = c("Aa", "Bb"))

I want the values of each row to be converted into different yaml file.

I expect each file to contain this:

State:
   type: string
   example: A
Cust_Age:
   type: number
   example: 25
City:
   type: string
   example: Aa

Similarly the second yaml file will contain values of second row of data frame.

You can use library(yaml). You need to cast your data.frame to a list structure first, which yaml::as.yaml can understand:

library(yaml)
library(purrr)
library(dplyr)
df <- data.frame(State = c("A", "B"),
                 Cust_Age = c(25, 50),
                 City = c("Aa", "Bb"))
ys <- df %>% 
   rowwise() %>% 
   group_map(function(x, y) {
      map(x, ~ list(type = case_when(is.factor(.x) | is.character(.x) ~ "string",
                                     is.numeric(.x) ~ "number", 
                                     is.logical(.x) ~ "logical", 
                                     TRUE ~ "unknown"),
                    example = .x)
      ) %>%
      as.yaml()
   })
 
cat(ys[[1L]])
# State:
#   type: string
#   example: A
# Cust_Age:
#   type: number
#   example: 25.0
# City:
#   type: string
#   example: Aa

cat(ys[[2L]])
# State:
#   type: string
#   example: B
# Cust_Age:
#   type: number
#   example: 50.0
# City:
#   type: string
#   example: Bb

If you expect other data types than string and number adapt your case_when accordingly (I added logical as a hypothetical example).

Note that as.yaml (correctly) transforms 25 to 25.0 because despite its appearance 25 ist not and integer. If you want 25 you should declare your numbers as integers by adding L:

cat(as.yaml(list(example = 25)))
# example: 25.0
cat(as.yaml(list(example = 25L)))
# example: 25