how to split rows of a dataframe in multiple rows based on start date and end date?

Question

I\'ve got a dataset with a starting date and an enddate, and I want to split the rows in this dataframe based on the year in the period. Take this data frame for example:

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Answer 1

Another approach could be

library(dplyr)
library(lubridate)

#sample data
df <- data.frame("starting_date" = as.Date(c("2015-06-01", "2013-06-01", "2016-02-11")),
                 "end_date" = as.Date(c("2017-09-30", "2017-11-11", "2017-01-01")),
                 col3=c('AAA','BBB', 'CCC'),
                 col4=c('33445454','565664', '123'))

df1 <- df[,1:2] %>% 
  rowwise() %>%
  do(rbind(data.frame(matrix(as.character(c(
    .$starting_date, 
    seq(.$starting_date, .$end_date, by=1)[grep("\\d{4}-12-31|\\d{4}-01-01", seq(.$starting_date, .$end_date, by=1))], 
    .$end_date)), ncol=2, byrow=T)))) %>%
  data.frame() %>%
  `colnames<-`(c("starting_date", "end_date")) %>%
  mutate(starting_date= as.Date(starting_date, format= "%Y-%m-%d"),
         end_date= as.Date(end_date, format= "%Y-%m-%d"))

#add temporary columns to the original and expanded date column dataframes
df$row_idx <- seq(1:nrow(df))
df$temp_col <- (year(df$end_date) - year(df$starting_date)) +1
df1 <- cbind(df1,row_idx = rep(df$row_idx,df$temp_col))

#join both dataframes to get the final result
final_df <- left_join(df1,df[,3:(ncol(df)-1)],by="row_idx") %>%
  select(-row_idx) 
final_df

Output is:

   starting_date   end_date col3     col4
1     2015-06-01 2015-12-31  AAA 33445454
2     2016-01-01 2016-12-31  AAA 33445454
3     2017-01-01 2017-09-30  AAA 33445454
4     2013-06-01 2013-12-31  BBB   565664
5     2014-01-01 2014-12-31  BBB   565664
6     2015-01-01 2015-12-31  BBB   565664
7     2016-01-01 2016-12-31  BBB   565664
8     2017-01-01 2017-11-11  BBB   565664
9     2016-02-11 2016-12-31  CCC      123
10    2017-01-01 2017-01-01  CCC      123