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I have two tables, both of which are aggregate outputs. I'd like to merge them together - they were both aggregated off the same data, so they have the same column names, but for the sake of edification I thought I'd try the specific by.x and by.y methods in the examples of ?merge.
merge(medA,countA,
by = c("manager_id", "manager_name", "grouping"))
## this works
merge(medA,countA,
by.x = c(medA$manager_id, medA$manager_name, medA$grouping),
by.y = c(countA$manager_id, countA$manager_name, countA$grouping))
## this doesn't?
## Error in fix.by(by.x, x) : 'by' must specify uniquely valid columns
It isn't particularly pressing: I can just use the merge that works. But I'm honestly confused why specific by.x and by.y doesn't work. I've googled around for it, but I can't seem to find similar problems. Any thoughts you guys have would be much appreciated.
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Merge data frames in R. The R merge function allows merging two data frames by common columns or by row names. This function allows you to perform different database (SQL) joins, like left join, inner join, right join or full join, among others.
In R we use merge() function to merge two dataframes in R. This function is present inside join() function of dplyr package. The most important condition for joining two dataframes is that the column type should be the same on which the merging happens. merge() function works similarly like join in DBMS.
How do I concatenate two columns in R? To concatenate two columns you can use the <code>paste()</code> function. For example, if you want to combine the two columns A and B in the dataframe df you can use the following code: <code>df['AB'] <- paste(df$A, df$B)</code>.
Join Multiple R DataFrames To join more than two (multiple) R dataframes, then reduce() is used. It is available in the tidyverse package which will convert all the dataframes to a list and join the dataframes based on the column.
Before using merge() also see if the classes of two tables you are trying to merge are same. If you try to merge data.table class with data.frame in that case also,it will throw this error.
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