Combine datasets using dplyr's bind and join functions
combine_data( x, y, by = "", add = "", type = "inner_join", data_filter = "", envir = parent.frame(), ... )
| x | Dataset |
|---|---|
| y | Dataset to combine with x |
| by | Variables used to combine `x` and `y` |
| add | Variables to add from `y` |
| type | The main bind and join types from the dplyr package are provided. inner_join returns all rows from x with matching values in y, and all columns from x and y. If there are multiple matches between x and y, all match combinations are returned. left_join returns all rows from x, and all columns from x and y. If there are multiple matches between x and y, all match combinations are returned. right_join is equivalent to a left join for datasets y and x. full_join combines two datasets, keeping rows and columns that appear in either. semi_join returns all rows from x with matching values in y, keeping just columns from x. A semi join differs from an inner join because an inner join will return one row of x for each matching row of y, whereas a semi join will never duplicate rows of x. anti_join returns all rows from x without matching values in y, keeping only columns from x. bind_rows and bind_cols are also included, as are intersect, union, and setdiff. See https://radiant-rstats.github.io/docs/data/combine.html for further details |
| data_filter | Expression used to filter the dataset. This should be a string (e.g., "price > 10000") |
| envir | Environment to extract data from |
| ... | further arguments passed to or from other methods |
Combined dataset
See https://radiant-rstats.github.io/docs/data/combine.html for an example in Radiant
avengers %>% combine_data(superheroes, type = "bind_cols")#> #> #> #> #> #> #>#> # A tibble: 7 x 8 #> name...1 alignment...2 gender...3 publisher...4 name...5 alignment...6 #> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 Thor good male Marvel Magneto bad #> 2 Iron Man good male Marvel Storm good #> 3 Hulk good male Marvel Mystique bad #> 4 Hawkeye good male Marvel Batman good #> 5 Black W… good female Marvel Joker bad #> 6 Captain… good male Marvel Catwoman bad #> 7 Magneto bad male Marvel Hellboy good #> # … with 2 more variables: gender...7 <chr>, publisher...8 <chr>combine_data(avengers, superheroes, type = "bind_cols")#> #> #> #> #> #> #>#> # A tibble: 7 x 8 #> name...1 alignment...2 gender...3 publisher...4 name...5 alignment...6 #> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 Thor good male Marvel Magneto bad #> 2 Iron Man good male Marvel Storm good #> 3 Hulk good male Marvel Mystique bad #> 4 Hawkeye good male Marvel Batman good #> 5 Black W… good female Marvel Joker bad #> 6 Captain… good male Marvel Catwoman bad #> 7 Magneto bad male Marvel Hellboy good #> # … with 2 more variables: gender...7 <chr>, publisher...8 <chr>avengers %>% combine_data(superheroes, type = "bind_rows")#> # A tibble: 14 x 4 #> name alignment gender publisher #> <chr> <chr> <chr> <chr> #> 1 Thor good male Marvel #> 2 Iron Man good male Marvel #> 3 Hulk good male Marvel #> 4 Hawkeye good male Marvel #> 5 Black Widow good female Marvel #> 6 Captain America good male Marvel #> 7 Magneto bad male Marvel #> 8 Magneto bad male Marvel #> 9 Storm good female Marvel #> 10 Mystique bad female Marvel #> 11 Batman good male DC #> 12 Joker bad male DC #> 13 Catwoman bad female DC #> 14 Hellboy good male Dark Horse Comicsavengers %>% combine_data(superheroes, add = "publisher", type = "bind_rows")#> # A tibble: 14 x 4 #> name alignment gender publisher #> <chr> <chr> <chr> <chr> #> 1 Thor good male Marvel #> 2 Iron Man good male Marvel #> 3 Hulk good male Marvel #> 4 Hawkeye good male Marvel #> 5 Black Widow good female Marvel #> 6 Captain America good male Marvel #> 7 Magneto bad male Marvel #> 8 Magneto bad male Marvel #> 9 Storm good female Marvel #> 10 Mystique bad female Marvel #> 11 Batman good male DC #> 12 Joker bad male DC #> 13 Catwoman bad female DC #> 14 Hellboy good male Dark Horse Comics