data.table join then add columns to existing data.frame without re-copy

by

This is easy to do:

X[Y, z := i.z]

It works because the only difference between Y[X] and X[Y] here, is when some elements are not in Y, in which case presumably you’d want z to be NA, which the above assignment will exactly do.

It would also work just as well for many variables:

X[Y, `:=`(z1 = i.z1, z2 = i.z2, ...)]

Since you require the operation Y[X], you can add the argument nomatch=0 (as @mnel points out) so as to not get NAs for those where X doesn’t contain the key values from Y. That is:

X[Y, z := i.z, nomatch=0]

From the NEWS for data.table

    **********************************************
    **                                          **
    **   CHANGES IN DATA.TABLE VERSION 1.7.10   **
    **                                          **
    **********************************************

NEW FEATURES

o   The prefix i. can now be used in j to refer to join inherited
    columns of i that are otherwise masked by columns in x with
    the same name.

More Related Contents:

  1. Understanding exactly when a data.table is a reference to (vs a copy of) another data.table
  2. Overlap join with start and end positions
  3. Left join using data.table
  4. Why does X[Y] join of data.tables not allow a full outer join, or a left join?
  5. R: data.table cross-join not working
  6. Rolling join on data.table with duplicate keys
  7. Update subset of data.table based on join
  8. Non-equi join using data.table: column missing from the output
  9. Conditional binary join and update by reference using the data.table package
  10. rolling joins data.table in R
  11. Convert a data frame to a data.table without copy
  12. Merging multiple data.tables
  13. Extract row corresponding to minimum value of a variable by group
  14. Pass column name in data.table using variable [duplicate]
  15. Using lists inside data.table columns
  16. Use merge() to update a data frame with values from a second data frame
  17. Select only the first row when merging data frames with multiple matches
  18. Find the intersection of overlapping ranges in two tables using data.table function foverlaps
  19. Referring to data.table columns by names saved in variables
  20. Calculate multiple aggregations on several variables using lapply(.SD, …)
  21. Merge rows in a dataframe where the rows are disjoint and contain NAs
  22. Calculate row-wise maximum
  23. Efficient row-wise operations on a data.table
  24. Replace logical values (TRUE / FALSE) with numeric (1 / 0)
  25. How to change type of target column when doing := by group in a data.table in R?
  26. Insert a row in a data.table
  27. Identify records in data frame A not contained in data frame B [closed]
  28. Efficiently merging two data frames on a non-trivial criteria
  29. assigning by reference into loaded package datasets
  30. calculating sum of previous 3 rows in R data.table (by grid-square)

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