---
title: "`data.table::merge()` wrapper"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{`data.table::merge()` wrapper}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{knitr::rmarkdown}
editor_options: 
  chunk_output_type: console
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}

library(joyn)
library(data.table)

 x1 = data.table(id = c(1L, 1L, 2L, 3L, NA_integer_),
                 t  = c(1L, 2L, 1L, 2L, NA_integer_),
                 x  = 11:15)
 y1 = data.table(id = c(1,2, 4),
                 y  = c(11L, 15L, 16))
 
 x2 = data.table(id1 = c(1, 1, 2, 3, 3),
                 id2 = c(1, 1, 2, 3, 4),
                 t   = c(1L, 2L, 1L, 2L, NA_integer_),
                 x   = c(16, 12, NA, NA, 15))
 
 y2 = data.table(id  = c(1, 2, 5, 6, 3),
                 id2 = c(1, 1, 2, 3, 4),
                 y   = c(11L, 15L, 20L, 13L, 10L),
                 x   = c(16:20))
 
```

This vignette describes the use of the `joyn` `merge()` function.

🔀 `joyn::merge` resembles the usability of `base::merge` and `data.table::merge`, while also incorporating the additional features that characterize `joyn`. In fact, `joyn::merge` masks the other two.

### Examples

#### Simple merge

Suppose you want to merge `x1` and `y1`. First notice that while `base::merge` is principally for data frames, `joyn::merge` coerces `x` and `y` to data tables if they are not already.

By default, `merge` will join by the shared column name(s) in `x` and `y`.

```{r ex1}

# Example not specifying the key
merge(x = x1, 
      y = y1)

# Example specifying the key
merge(x = x1, 
      y = y1,
      by = "id")

```

As usual, if the columns you want to join by don’t have the same name, you need to tell merge which columns you want to join by: `by.x` for the x data frame column name, and `by.y` for the y one. For example,

```{r ex2}

df1 <- data.frame(id = c(1L, 1L, 2L, 3L, NA_integer_, NA_integer_),
                  t  = c(1L, 2L, 1L, 2L, NA_integer_, 4L),
                  x  = 11:16)

df2 <- data.frame(id = c(1,2, 4, NA_integer_, 8),
                  y  = c(11L, 15L, 16, 17L, 18L),
                  t  = c(13:17))

merge(x    = df1,
      y    = df2,
      by.x = "x",
      by.y = "y")

```

By default, `sort` is `TRUE`, so that the merged table will be sorted by the `by.x` column. Notice that the output table distinguishes non-by column *t* coming from `x` from the one coming from `y` by adding the *.x* and *.y* suffixes -which occurs because the `no.dups` argument is set to `TRUE` by default.

#### Going further

In a similar fashion as the `joyn()` primary function does, `merge()` offers a number of arguments to verify/control the merge[^1].

[^1]: See the "Advanced functionalities" article for more details

For example, `joyn::joyn` allows to execute one-to-one, one-to-many, many-to-one and many-to-many joins. Similarly, `merge` accepts the `match_type` argument:

```{r ex3}

# Example with many to many merge
joyn::merge(x          = x2,
            y          = y2,
            by.x       = "id1",
            by.y       = "id2",
            match_type = "m:m")

# Example with many to many merge
joyn::merge(x          = x1,
            y          = y1,
            by         = "id",
            match_type = "m:1")


```

In a similar way, you can exploit all the other additional options available in `joyn()`, e.g., for keeping common variables, updating NAs and values, displaying messages etc..., which you can explore in the "Advanced functionalities" article.
