Change on joins vignette

vignettes/datatable-intro.Rmd

@@ -95,7 +95,7 @@ You can also convert existing objects to a `data.table` using `setDT()` (for `da
     getOption("datatable.print.nrows")
     ```
 
-* `data.table` doesn't set or use *row names*, ever. We will see why in the *Keys and fast binary search based subset* vignette.
+* `data.table` doesn't set or use *row names*, ever. We will see why in the [`vignette("datatable-keys-fast-subset", package="data.table")`](datatable-keys-fast-subset.html) vignette.
 
 ### b) General form - in what way is a `data.table` *enhanced*? {#enhanced-1b}
 
@@ -473,7 +473,7 @@ ans
 
 **Keys:** Actually `keyby` does a little more than *just ordering*. It also *sets a key* after ordering by setting an `attribute` called `sorted`. 
 
-We'll learn more about `keys` in the *Keys and fast binary search based subset* vignette; for now, all you have to know is that you can use `keyby` to automatically order the result by the columns specified in `by`.
+We'll learn more about `keys` in the [`vignette("datatable-keys-fast-subset", package="data.table")`](datatable-keys-fast-subset.html) vignette; for now, all you have to know is that you can use `keyby` to automatically order the result by the columns specified in `by`.
 
 ### c) Chaining
 
@@ -682,7 +682,7 @@ We have seen so far that,
 
 * We can also sort a `data.table` using `order()`, which internally uses data.table's fast order for better performance.
 
-We can do much more in `i` by keying a `data.table`, which allows for blazing fast subsets and joins. We will see this in the vignettes *Keys and fast binary search based subset* and *`data.table joins`*.
+We can do much more in `i` by keying a `data.table`, which allows for blazing fast subsets and joins. We will see this in the vignettes [`vignette("datatable-keys-fast-subset", package="data.table")`](datatable-keys-fast-subset.html) and [`vignette("datatable-joins", package="data.table")`](datatable-joins.html).
 
 #### Using `j`:
 

vignettes/datatable-joins.Rmd

@@ -5,8 +5,8 @@ output:
   litedown::html_format
 vignette: >
   %\VignetteIndexEntry{Joins in data.table}
-  %\VignetteEngine{litedown::vignette}
   \usepackage[utf8]{inputenc}
+  %\VignetteEngine{litedown::vignette}
 editor_options: 
   chunk_output_type: console
 ---
@@ -27,6 +27,7 @@ It assumes familiarity with the `data.table` syntax. If that is not the case, pl
 - [`vignette("datatable-intro", package="data.table")`](datatable-intro.html)
 - [`vignette("datatable-reference-semantics", package="data.table")`](datatable-reference-semantics.html)
 - [`vignette("datatable-keys-fast-subset", package="data.table")`](datatable-keys-fast-subset.html)
+- [`vignette("datatable-secondary-indices-and-auto-indexing", package="data.table")`](datatable-secondary-indices-and-auto-indexing.html)
 
 ***
 

vignettes/datatable-reference-semantics.Rmd

@@ -265,7 +265,7 @@ head(flights)
 ```{r}
 flights[, names(.SD) := lapply(.SD, as.factor), .SDcols = is.character]
 ```
-Let's clean up again and convert our newly-made factor columns back into character columns. This time we will make use of `.SDcols` accepting a function to decide which columns to include. In this case, `is.factor()` will return the columns which are factors. For more on the **S**ubset of the **D**ata, there is also an [SD Usage vignette](https://cran.r-project.org/package=data.table/vignettes/datatable-sd-usage.html).
+Let's clean up again and convert our newly-made factor columns back into character columns. This time we will make use of `.SDcols` accepting a function to decide which columns to include. In this case, `is.factor()` will return the columns which are factors. For more on the **S**ubset of the **D**ata, there is also an [SD Usage vignette ('vignette("datatable-sd-usage", package="data.table")')](datatable-sd-usage.html).
 
 Sometimes, it is also nice to keep track of columns that we transform. That way, even after we convert our columns we would be able to call the specific columns we were updating.
 ```{r}

vignettes/es/datatable-joins.Rmd

@@ -28,6 +28,7 @@ Se presupone familiaridad con la sintaxis de `data.table`. De no ser así, lea l
 - [`viñeta("datatable-intro", paquete="data.table")`](datatable-intro.html)
 - [`viñeta("datatable-reference-semantics", paquete="data.table")`](datatable-reference-semantics.html)
 - [`viñeta("datatable-keys-fast-subset", paquete="data.table")`](datatable-keys-fast-subset.html)
+- [`viñeta("datatable-secondary-indices-and-auto-indexing", paquete="data.table")`](datatable-secondary-indices-and-auto-indexing.html)
 
 ***
 

vignettes/es/datatable-reference-semantics.Rmd

@@ -270,7 +270,7 @@ head(flights)
 flights[, names(.SD) := lapply(.SD, as.factor), .SDcols = is.character]
 ```
 
-Limpiemos de nuevo y convirtamos nuestras columnas de factores recién creadas en columnas de caracteres. Esta vez, usaremos `.SDcols`, que acepta una función para decidir qué columnas incluir. En este caso, `is.factor()` devolverá las columnas que son factores. Para más información sobre el **S**subconjunto de **D**atos, también hay una viñeta de uso de SD (https://cran.r-project.org/package=data.table/vignettes/datatable-sd-usage.html).
+Limpiemos de nuevo y convirtamos nuestras columnas de factores recién creadas en columnas de caracteres. Esta vez, usaremos `.SDcols`, que acepta una función para decidir qué columnas incluir. En este caso, `is.factor()` devolverá las columnas que son factores. Para más información sobre el **S**ubconjunto de **D**atos, también hay una [viñeta de uso de SD ('vignette("datatable-sd-usage", package="data.table")')](datatable-sd-usage.html).
 
 A veces, también es útil llevar un registro de las columnas que transformamos. De esta manera, incluso después de convertirlas, podremos llamar a las columnas específicas que actualizamos.
 

vignettes/fr/datatable-joins.Rmd

@@ -27,6 +27,7 @@ Cela suppose que vous êtes déjà familiarisé avec la syntaxe `data.table` . S
 - [`vignette("datatable-intro", package="data.table")`](datatable-intro.html)
 - [`vignette("datatable-reference-semantics", package="data.table")`](datatable-reference-semantics.html)
 - [`vignette("datatable-keys-fast-subset", package="data.table")`](datatable-keys-fast-subset.html)
+- [`vignette("datatable-secondary-indices-and-auto-indexing", package="data.table")`](datatable-secondary-indices-and-auto-indexing.html)
 
 ***
 

vignettes/fr/datatable-reference-semantics.Rmd

@@ -269,7 +269,7 @@ head(flights)
 flights[, names(.SD) := lapply(.SD, as.factor), .SDcols = is.character]
 ```
 
-Nettoyons à nouveau et convertissons nos colonnes de facteurs nouvellement créées en colonnes de caractères. Cette fois, nous allons utiliser `.SDcols` qui accepte une fonction pour décider quelles colonnes inclure. Dans ce cas, `is.factor()` retournera les colonnes qui sont des facteurs. Pour en savoir plus sur le **S**ous-ensemble des **D**onnées (**S**ubset of the **D**ata), il y a aussi une [vignette sur l’utilisation de SD](https://cran.r-project.org/package=data.table/vignettes/datatable-sd-usage.html).
+Nettoyons à nouveau et convertissons nos colonnes de facteurs nouvellement créées en colonnes de caractères. Cette fois, nous allons utiliser `.SDcols` qui accepte une fonction pour décider quelles colonnes inclure. Dans ce cas, `is.factor()` retournera les colonnes qui sont des facteurs. Pour en savoir plus sur le **S**ous-ensemble des **D**onnées (**S**ubset of the **D**ata), il y a aussi une [vignette sur l’utilisation de SD ('vignette("datatable-sd-usage", package="data.table")')](datatable-sd-usage.html)
 
 Parfois, il est également utile de garder une trace des colonnes que nous transformons. Ainsi, même après avoir converti nos colonnes, nous pourrons toujours appeler les colonnes spécifiques que nous avons mises à jour.