I have a table of the following format:
And I'm seeking an output resembling the following:
| Date | Value |
|---|---|
| January 1659 | Value 1 |
| February 1659 | Value 2 |
| March 1659 | Value 3 |
| April 1659 | Value 4 |
and so on (numerical representations of the Month and Year are perfectly fine also.
I've attempted using merge operations but I'm thinking there must be an easier way (possibly using packages). I've found somewhat similar questions asked but none obviously applicable yet.
You can use pivot_longer and unite, both from the tidyr package:
library(tidyr)
pivot_longer(df, -Year) |>
unite(date, name, Year, sep = " ")
#> # A tibble: 120 x 2
#> date value
#> <chr> <int>
#> 1 Jan 1659 68
#> 2 Feb 1659 97
#> 3 Mar 1659 89
#> 4 Apr 1659 74
#> 5 May 1659 44
#> 6 Jun 1659 2
#> 7 Jul 1659 81
#> 8 Aug 1659 22
#> 9 Sep 1659 87
#> 10 Oct 1659 1
#> # ... with 110 more rows
Data used
set.seed(1)
df <- cbind(1659:1668, replicate(12, sample(99, 10))) |>
as.data.frame() |>
setNames(c("Year", month.abb))
df
#> Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
#> 1 1659 68 97 89 74 44 2 81 22 87 1 76 43
#> 2 1660 39 85 37 42 25 45 13 93 83 43 39 1
#> 3 1661 1 21 34 38 70 18 40 28 90 59 24 29
#> 4 1662 34 54 99 20 39 22 89 48 48 26 53 78
#> 5 1663 87 74 44 28 51 78 48 33 64 15 92 22
#> 6 1664 43 7 79 96 42 65 96 45 94 58 86 70
#> 7 1665 14 73 33 44 6 70 23 21 60 29 40 28
#> 8 1666 82 79 84 87 24 87 84 31 51 24 83 37
#> 9 1667 59 98 35 70 32 93 29 17 34 42 90 61
#> 10 1668 51 37 70 40 14 75 98 73 10 48 35 46
Created on 2022-11-29 with reprex v2.0.2
