Data transformation when only one digit differs with R

user_12538121 0
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I am new to R and need help with the following task. In the table below is a dummy example of data. I am struggling with writing a script that should change the price, if only one price is different (for a particular ppcode, in this example is 4th) and only one symbol in that price differs compared with the majority, to the same number as other prices. In this example, 1.42 should be changed to 1.45. But also if instead of 1.42 would be, for example, 1.55 it also should be changed to 1.45, or when 2.45 to 1.45 (in all cases when only one digit of a price differs).
Thanks in advance for any suggestions.

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dataframe numbers r
3 Answers

If we need the Mode value, an option with dplyr is

Mode <- function(x) {
  ux <- unique(x)
  ux[which.max(tabulate(match(x, ux)))]
}

library(dplyr)
df1 <- df1 %>%
        group_by(PPCODE, grp = sprintf('%.1f', PRICE)) %>%
        mutate(PRICE = Mode(PRICE)) %>%
        ungroup %>%
        select(-grp)
user_37322710

Here is a base R way with ave.

with(df1, ave(PRICE, PPCODE, FUN = \(x) x[which.max(table(x))]))
#[1] 1.45 1.45 1.45 1.45

And just assign the result back to PRICE.

df1$PRICE <- with(df1, ave(PRICE, PPCODE, FUN = \(x) x[which.max(table(x))]))
user_82454060

Here is a dplyr way:

library(dplyr)
df %>% 
  group_by(PRICE) %>% 
  mutate(helper = n()) %>% 
  ungroup() %>% 
  group_by(PPCODE) %>% 
  mutate(PRICE = ifelse(helper == unique(1), first(PRICE), PRICE), .keep="unused")

output:

  OUTLETID   CAT     PPCODE PRICE
  <chr>      <chr>    <int> <dbl>
1 8900NS2871 AIR   46239679  1.45
2 8900NX2201 AIR   46239679  1.45
3 8900NK2202 AIR   46239679  1.45
4 8900NV1594 AIR   46239679  1.45
user_133216470
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