在时间序列数据中插入缺失的行

Question

I have an incomplete time series dataframe and I need to insert rows of NAs for missing time stamps. There should always be 6 time stamps per day, which is indicated by the variable "Signal" (1-6) in the dataframe. I am trying to merge the incomplete dataframe A with a vector B containing all Signals. Simplified example data below:

B <- rep(1:6,2) 
A <- data.frame(Signal = c(1,2,3,5,1,2,4,5,6), var1 = c(1,1,1,1,1,1,1,1,1))
Expected <- data.frame(Signal = c(1,2,3,NA, 5, NA, 1,2,NA,4,5,6), var1 = c(1,1,1,NA,1,NA,1,1,NA,1,1,1)

Note that B represents a dataframe with multiple variables and the NAs in Expected are rows of NAs in the dataframe. Also the actual dataframe has more observations (84 in total).

Would be awesome if you guys could help me out!

Answer 1

If you already know there are 6 timestamps in a day you can do this without B . We can create groups for each day and use complete to add the missing observations with NA .

library(dplyr)
library(tidyr)

A %>%
  group_by(gr = cumsum(c(TRUE, diff(Signal) < 0))) %>%
  complete(Signal = 1:6) %>%
  ungroup() %>%
  select(-gr)

#   Signal  var1
#    <dbl> <dbl>
# 1      1     1
# 2      2     1
# 3      3     1
# 4      4    NA
# 5      5     1
# 6      6    NA
# 7      1     1
# 8      2     1
# 9      3    NA
#10      4     1
#11      5     1
#12      6     1

If in the output you need Signal as NA for missing combination you can use

A %>%
  group_by(gr = cumsum(c(TRUE, diff(Signal) < 0))) %>%
  complete(Signal = 1:6) %>%
  mutate(Signal = replace(Signal, is.na(var1), NA)) %>%
  ungroup %>%
  select(-gr)

#   Signal  var1
#    <dbl> <dbl>
# 1      1     1
# 2      2     1
# 3      3     1
# 4     NA    NA
# 5      5     1
# 6     NA    NA
# 7      1     1
# 8      2     1
# 9     NA    NA
#10      4     1
#11      5     1
#12      6     1