Add rows corresponding to missing dates in a dataframe

Asked Mar 14 '19 at 15:14

Active May 28 '19 at 07:14

Viewed 37 times

I have a dataframe with 2 variables and multiple Product_Ids. For some Ids, some dates are missing.

library(dplyr)

df <- data.frame(Product_Id = rep(1:100, each = 50), 
                 Date = seq(from = as.Date("2008/1/1"), to = as.Date("2018/2/1") , by = "month"), 
                 Sales = rnorm(100, mean = 50, sd= 20))
df <- df[-c(1,4,67,78,251:256, 301:312, 2551:2562, 2651:2662, 2751:2762), ]
x <- count(df, vars = Product_Id)
View(df)

Is there anyway to create a dataframe which contains all the Dates in the right sequence along with the Product_Id and empty cells corresponding to Sales?

edited May 28 '19 at 07:14

asked Mar 14 '19 at 15:14

user10579790

2

What's the right sequence? – NelsonGon Mar 14 '19 at 15:18
2

`tidyr::complete(df, Product_Id, Date)` should be what you're looking for. This gives `NA` for the Sales values. – kath Mar 14 '19 at 15:22

Add rows corresponding to missing dates in a dataframe

0 Answers0