2
I am starting in R, and I have a data frame similar to this one below:
x <- data.frame(cod_produto = c(1,1,1,2,2,2),
valordia = c(0,0,150.23,110.98,18.65,0),
data = c("2019-01-01","2019-01-02","2019-01-03","2019-01-01","2019-01-02","2019-01-03"))
How to return the first day the sale took place (valordia > 0)?
I tried to use the package dplyr.
2
With dplyr:
library(dplyr)
x %>%
filter(valordia > 0) %>%
arrange(data) %>%
slice(1)
cod_produto valordia data
2 110.98 2019-01-01
filter filters the values > 0;
arrange sorts the dates;
slice returns only the first observation, in this case.
If you want to know when the first sale took place, no matter the date, just remove the arrange function. It would look like this:
x %>%
filter(valordia > 0) %>%
slice(1)
cod_produto valordia data
1 150.23 2019-01-03
0
With R base can be as follows.
First transform the column data in a class column "Date".
x$data <- as.Date(x$data)
Now, first get an index of the table rows ordered by date and then extract the smallest row with valordia > 0.
i <- order(x$data)
x[i, ][min(which(x$valordia[i] > 0)), ]
# cod_produto valordia data
#4 2 110.98 2019-01-01
Rui, thanks for the feedback.
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Thanks for the return. There is possibility to use within a Summarize?
– Ceconello
How would the use (for example, add the
valordia)?– neves
Something similar to the code below. Somando o valor total das vendas e incluindo dois campos com a data da primeira e da última venda:

y <- x %>% 
 dplyr::group_by(cod_produto) %>%
 dplyr::summarize(totalVenda = sum(valordia),
 dataPrimeiraVenda = ??? , dataUltimaVenda = ???)
– Ceconello
Instead of
summarisewhich returns a simple summary of an operation, usemutate. Make sure you answer to what you want:y <- x %>% 
 group_by(cod_produto) %>% 
 mutate(totalVenda = sum(valordia)) %>% 
 arrange(data) %>% 
 slice(c(1, n()))– neves
The code you created returns two lines for each product (first date and last date). However, what I need is to group by product code (that’s why I was using the
summarise). The result would look something like this (in single record for each product):cod_produto,totalVenda,dataPrimeiraVenda,dataUltimaVenda. The dates of the first and last sale must be by fieldvalordia > 0– Ceconello
Do you want the date in separate columns? This is,
dataPrimeiraVendaanddataUltimaVendaand, if thevalordia > 0? If so, it follows:library(tidyr)

x %>% group_by(cod_produto) %>% 
 mutate(totalVenda = sum(valordia)) %>% 
 arrange(data) %>% 
 slice(c(1, n())) %>% 
 spread(key = data, value = totalVenda) %>% 
 filter(valordia > 0). ThetotalVendais inside the dated columns.– neves
For the question date frame, the result should be like this:
structure(data.frame(cod_produto = c(1,2),totalVenda = c(150.23,129.63), dataPrimeiraVenda = c("2019-01-03","2019-01-01"), dataUltimaVenda = c("2019-01-03","2019-01-02")))– Ceconello