I need to compare the superior row with the one below, so I can create an empty one or with the infeiror's content, depending on that comparison

Question

In R, I need to creat the colums "codigo", "color", "talle", "lista","precio" in the right using the values of the some ones of the left. What I want to do is that when the value of "codigo" of the inferior row is the same as the superior row and the value of "precio" of the inferior row is the some as the superior row, all the inferior row must be empty, however, if "precio" changes, then the infirior row must show its value of, and only, "codigo", "talle" and "precio". If the value of "codigo" of the inferior row compared with the superior row is different, then the inferior row must have the value of "codigo" and "precio", and then repete the procedure all over again till the end of the rows.

clearley I don´t have enough knowledge to do this, I´ve tried this:

    preciosdupli2<- df %>% group_by(Artículo,Talle,LISTA1) %>% filter (!duplicated(Artículo,Talle,LISTA1)

and also this:

    talleunico<-df%>%distinct(Talle) preciosdupli2<- df %>% group_by(Artículo,Talle,LISTA1) %>% filter (!duplicated(Artículo,Talle==talleunico,LISTA1))

codigo	color	talle	lista	precio		codigo	color	talle	lista	precio
26	GRIS	1	LISTA1	9890		26				9890
26	NEGR	1	LISTA1	9890
26		2	LISTA1	9890
26	ACQU	2	LISTA1	9890
26	AZUL	2	LISTA1	9890
26	GRIS	2	LISTA1	9890
26	NEGR	3	LISTA1	9890
26	ROJO	4	LISTA1	12202		26	4			12202
26	SALM	5	LISTA1	12203		26	5			12203
28	GRIS	1	LISTA1	2150		28				2150
29	AZUL	1	LISTA1	2390		29				2390
29	ROJO	2	LISTA1	2390
29	VERD	3	LISTA1	2390
29	VIOL	4	LISTA1	2500		29	4			2500
29	AZUL	5	LISTA1	3300		29	5			3300
29	ROJO	6	LISTA1	3300		29	6			3300
29	VERD	6	LISTA1	3300		29	6			3300
29	VIOL	7	LISTA1	3333		29	7			3333

Answer 1

It's a little hard to work out the logical conditions from the text. Is the inferior row the previous row? Is the superior row the current or next row?

Here's a bit of code that might get you started:

library(dplyr)

data <- read.csv("./73739092/data.csv")

data2 <- data %>%
  mutate(codigo_2 = if_else(lag(precio, 1) != precio |
                              is.na(lag(precio, 1)), codigo, 0L))

Expand on the logical conditions and you may get where you need to be. Note that you should really offer a reproducible example, for instance see here . I had to copy your data into a csv file and read it into R.