How can find the row indices in one data frame where its values exist in another sorther data frame?

[Beata]

Dear R Users,

I have two data frame. Each of them has three columns but the number of rows is different. I would like to find the row indices of the longer data frame where its values exist in the other data frame. I tried the following:

ind = which(as.numeric(Results[,1]) 
                   %in% as.numeric(Hour.mean[,1]) 
                   & as.numeric(Results[,2]) %in% as.numeric(Hour.mean[,2]) 
                   & as.numeric(Results[,3]) %in% as.numeric(Hour.mean[,3])
)

but it does not give correct values. Could someone suggest me a solution?

[andresrcs]

Hi!

To help us help you, could you please prepare a reproducible example (reprex) illustrating your issue? Please have a look at this guide, to see how to create one:

FAQ: How to do a minimal reproducible example ( reprex ) for beginners

A minimal reproducible example consists of the following items: A minimal dataset, necessary to reproduce the issue The minimal runnable code necessary to reproduce the issue, which can be run on the given dataset, and including the necessary information on the used packages. Let's quickly go over each one of these with examples: Minimal Dataset (Sample Data) You need to provide a data frame that is small enough to be (reasonably) pasted on a post, but big enough to reproduce your issue. Let's say, as an example, that you are working with the iris data frame head(iris) #> Sepal.Length Sepal.Width Petal.Length Petal.Width Species #> 1 5.1 3.5 1.4 0.2…

[Beata]

Meantime I found a solution. I converted the column values of Results and also the Hour.mean with past function and then I could find the row indices with which function with the following way:

List1 = paste(Results[,1], Results[,2], Results[,3], sep=".")
List2 = paste(Hour.mean[,1], Hour.mean[,2], Hour.mean[,3], sep=".")
ind = which(List1 %in% List2)