Cartesian product with dplyr

by

Use crossing from the tidyr package: 

x <- data.frame(x=c("a","b","c"))
y <- data.frame(y=c(1,2,3))

crossing(x, y)

Result: 

   x y
 1 a 1
 2 a 2
 3 a 3
 4 b 1
 5 b 2
 6 b 3
 7 c 1
 8 c 2
 9 c 3

More Related Contents:

  1. Gather multiple sets of columns
  2. How to get summary statistics by group
  3. Is there a dplyr equivalent to data.table::rleid?
  4. Replace NA with previous or next value, by group, using dplyr
  5. Filter rows which contain a certain string
  6. Calculate group mean, sum, or other summary stats. and assign column to original data
  7. Rolling mean (moving average) by group/id with dplyr
  8. Programming with dplyr using string as input
  9. Count number of rows by group using dplyr
  10. Pass a vector of variable names to arrange() in dplyr
  11. How to remove rows with any zero value
  12. Efficient way to filter one data frame by ranges in another
  13. R – add column that counts sequentially within groups but repeats for duplicates
  14. Categorize numeric variable with mutate
  15. Means multiple columns by multiple groups [duplicate]
  16. How to aggregate a dataframe by week?
  17. How to use map from purrr with dplyr::mutate to create multiple new columns based on column pairs
  18. Conditional cumsum with reset
  19. How to speed up subset by groups
  20. Use rle to group by runs when using dplyr
  21. Number of significant digits in dplyr summarise
  22. Calculate group mean while excluding current observation using dplyr
  23. Emulate split() with dplyr group_by: return a list of data frames
  24. Sparklyr: how to center a Spark table based on column?
  25. R: x ‘probs’ outside [0,1]
  26. dplyr::mutate to add multiple values
  27. Canonical tidyverse method to update some values of a vector from a look-up table
  28. Spreading a two column data frame with tidyr
  29. R dplyr rowwise mean or min and other methods?
  30. Collapse all columns by an ID column [duplicate]

Leave a Comment