I have a dataframe that contains two columns X-data and Y-data. This represents some experimental data.
Now I have a lot of additional information that I want to associate with this data, such as temperatures, flow rates and so on the sample was recorded at. I have this metadata in a second dataframe.
The data and metadata should always stay together, but I also want to be able to do calculations with the data
As I have many of those data-metadata pairs (>100), I was wondering what people think is an efficient way to organize the data?
For now, I have the two dataframes in a list, but I find accessing the individual values or data-columns tedious (= a lot of code and brackets to write).
You can use an attribute:
dfr <- data.frame(x=1:3,y=rnorm(3))
meta <- list(temp="30C",date=as.Date("2013-02-27"))
attr(dfr,"meta") <- meta
dfr
x y
1 1 -1.3580532
2 2 -0.9873850
3 3 0.3809447
attr(dfr,"meta")
$temp
[1] "30C"
$date
[1] "2013-02-27"
str(dfr)
'data.frame': 3 obs. of 2 variables:
$ x: int 1 2 3
$ y: num -1.358 -0.987 0.381
- attr(*, "meta")=List of 2
..$ temp: chr "30C"
..$ date: Date, format: "2013-02-27"