Insert rows with no values

Question

The data is similar to:

 quarter name  week  value
 17Q3    abc   1     0.7
 17Q3    abc   3     0.65
 17Q3    def   1     0.13
 17Q3    def   2     0.04

Is it possible to insert rows with value = 0, where there are no values ​​for the week ie the output should look like this:

quarter name  week  value
 17Q3    abc   1     0.7
 17Q3    abc   3     0.65
 17Q3    abc   2     0.0
 17Q3    def   1     0.13
 17Q3    def   2     0.04
 17Q3    def   3     0.0

must be completed before the 13th week. (i.e. up to 13)

Answer 1

How about using expandinside complete.

library(tidyverse)
complete(df, expand(df, quarter, name, week), fill = list(value=0))

#   quarter name   week  value
#   <fct>   <fct> <int>  <dbl>
# 1 17Q3    abc       1 0.700 
# 2 17Q3    abc       2 0     
# 3 17Q3    abc       3 0.650 
# 4 17Q3    def       1 0.130 
# 5 17Q3    def       2 0.0400
# 6 17Q3    def       3 0   

Or maybe it’s easier to understand:

df %>% expand(quarter, name, week) %>% left_join(df) %>% replace_na(list(value=0))

Answer 2

Here is one of the options with tidyverse. We get the missing combination of rows with complete, arrangerows based on "quarter", "name" and "id", then mutate"id" on "row_number ()) select` andcolumns have the same order as in the original dataset

library(tidyverse)
df1 %>%
  complete(quarter, name, week = full_seq(week, 1), fill = list(value = 0)) %>%
  arrange(quarter, name, id) %>%
  mutate(id = row_number()) %>% 
  select(names(df1))
# A tibble: 6 x 5
#     id quarter name   week  value
#  <int> <chr>   <chr> <dbl>  <dbl>
#1     1 17Q3    abc    1.00 0.700 
#2     2 17Q3    abc    3.00 0.650 
#3     3 17Q3    abc    2.00 0     
#4     4 17Q3    def    1.00 0.130 
#5     5 17Q3    def    2.00 0.0400
#6     6 17Q3    def    3.00 0