R time series missing values

Question

I was working with a time series dataset having hourly data. The data contained a few missing values so I tried to create a dataframe (time_seq) with the correct time value and do a merge with the original data so the missing values become 'NA'.

> data

     date                 value
7980 2015-03-30 20:00:00  78389
7981 2015-03-30 21:00:00  72622
7982 2015-03-30 22:00:00  65240
7983 2015-03-30 23:00:00  47795
7984 2015-03-31 08:00:00  37455
7985 2015-03-31 09:00:00  70695 
7986 2015-03-31 10:00:00  68444

//converting the date in the data to POSIXct format.

> data$date <- format.POSIXct(data$date,'%Y-%m-%d %H:%M:%S') 

// creating a dataframe with the correct sequence of dates. 

> time_seq <- seq(from = as.POSIXct("2014-05-01 00:00:00"), 
              to = as.POSIXct("2015-04-30 23:00:00"), by = "hour")

> df <- data.frame(date=time_seq)

> df 

     date            
8013 2015-03-30 20:00:00
8014 2015-03-30 21:00:00
8015 2015-03-30 22:00:00
8016 2015-03-30 23:00:00
8017 2015-03-31 00:00:00
8018 2015-03-31 01:00:00
8019 2015-03-31 02:00:00
8020 2015-03-31 03:00:00
8021 2015-03-31 04:00:00
8022 2015-03-31 05:00:00
8023 2015-03-31 06:00:00
8024 2015-03-31 07:00:00

// merging with the original data

> a <- merge(data,df, x.by = data$date, y.by = df$date ,all=TRUE)

> a    
       date                 value
 4005  2014-07-23 07:00:00   37003
 4006  2014-07-23 07:30:00       NA
 4007  2014-07-23 08:00:00   37216
 4008  2014-07-23 08:30:00       NA

The values I get after merging are incorrect and they contain half-hourly values. What would be the correct approach for solving this?

Why are is the merge result in 30 minute intervals when both my dataframes are hourly?

PS:I looked into this question : Fastest way for filling-in missing dates for data.table and followed the steps but it didn't help.

Answer 1

You can use the padr package to solve this problem.

library(padr)
library(dplyr) #for the pipe operator
data %>%
  pad() %>%
  fill_by_value()