Single row per id to multiple row per id

Question

I'd like to expand observations from single row-per-id to multiple rows-per-id based on a given time interval:

> dput(df)
structure(list(id = c(123, 456, 789), gender = c(0, 1, 1), yr.start = c(2005, 
2010, 2000), yr.last = c(2007, 2012, 2000)), .Names = c("id", 
"gender", "yr.start", "yr.last"), class = c("tbl_df", "tbl", 
"data.frame"), row.names = c(NA, -3L))
> df
# A tibble: 3 x 4
     id gender yr.start yr.last
  <dbl>  <dbl>    <dbl>   <dbl>
1   123      0     2005    2007
2   456      1     2010    2012
3   789      1     2000    2000

I want to get id expanded into one row per year:

> dput(df_out)
structure(list(id = c(123, 123, 123, 456, 456, 456, 789), gender = c(0, 
0, 0, 1, 1, 1, 1), yr = c(2005, 2006, 2007, 2010, 2011, 2012, 
2000)), .Names = c("id", "gender", "yr"), class = c("tbl_df", 
"tbl", "data.frame"), row.names = c(NA, -7L))
> df_out
# A tibble: 7 x 3
     id gender    yr
  <dbl>  <dbl> <dbl>
1   123      0  2005
2   123      0  2006
3   123      0  2007
4   456      1  2010
5   456      1  2011
6   456      1  2012
7   789      1  2000

I know how to melt/reshape, but I'm not sure how I can expand the years. Thanks.

Answer 1

这是基本的R方法。

# expand years to a list
yearList <- mapply(":", df$yr.start, df$yr.last)

现在，使用此列表计算每个ID（的第二个参数rep）要重复的行数，然后使用将其附加为向量（从列表转换为unlist）cbind。

# get data.frame
cbind(df[rep(seq_along(df$id), lengths(yearList)), c("id", "gender")], yr=unlist(yearList))
     id gender   yr
1   123      0 2005
1.1 123      0 2006
1.2 123      0 2007
2   456      1 2010
2.1 456      1 2011
2.2 456      1 2012
3   789      1 2000