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mattdowle merged 1 commit into from
May 24, 2019
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Follow-up to #3572 #3593

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6 changes: 3 additions & 3 deletions vignettes/datatable-sd-usage.Rmd
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Original file line number Diff line number Diff line change
Expand Up @@ -169,15 +169,15 @@ lm_coef = sapply(models, function(rhs) {
Pitching[ , coef(lm(ERA ~ ., data = .SD))['W'], .SDcols = c('W', rhs)]
})
barplot(lm_coef, names.arg = sapply(models, paste, collapse = '/'),
main = 'Wins Coefficient\nWiith Various Covariates',
main = 'Wins Coefficient\nWith Various Covariates',
col = col16, las = 2L, cex.names = .8)
```

The coefficient always has the expected sign (better pitchers tend to have more wins and fewer runs allowed), but the magnitude can vary substantially depending on what else we control for.

## Conditional Joins

`data.table` syntax is beautiful for its simplicity and robustness. The syntax `x[i]` flexibly handles two common approaches to subsetting -- when `i` is a `logical` vector, `x[i]` will return those rows of `x` corresponding to where `i` is `TRUE`; when `i` is _another `data.table`_, a (right) `join` is performed (in the plain form, using the `key`s of `x` and `i`, otherwise, when `on = ` is specified, using matches of those columns).
`data.table` syntax is beautiful for its simplicity and robustness. The syntax `x[i]` flexibly handles three common approaches to subsetting -- when `i` is a `logical` vector, `x[i]` will return those rows of `x` corresponding to where `i` is `TRUE`; when `i` is _another `data.table`_ (or a `list`), a (right) `join` is performed (in the plain form, using the `key`s of `x` and `i`, otherwise, when `on = ` is specified, using matches of those columns); and when `i` is a character, it is interpreted as shorthand for `x[list(i)]`, i.e., as a join.

This is great in general, but falls short when we wish to perform a _conditional join_, wherein the exact nature of the relationship among tables depends on some characteristics of the rows in one or more columns.

Expand Down Expand Up @@ -235,7 +235,7 @@ Teams[ , .SD[which.max(R)], by = teamID]

Note that this approach can of course be combined with `.SDcols` to return only portions of the `data.table` for each `.SD` (with the caveat that `.SDcols` should be fixed across the various subsets)

_NB_: `.SD[1L]` is currently optimized by [_`GForce`_](https://jangorecki.gitlab.io/data.table/library/data.table/html/datatable-optimize.html) ([see also](https://stackoverflow.com/questions/22137591/about-gforce-in-data-table-1-9-2)), `data.table` internals which massively speed up the most common grouped operations like `sum` or `mean` -- see `?GForce` for more details and keep an eye on/voice support for feature improvement requests for updates on this front: [1](https://github.com/Rdatatable/data.table/issues/735), [2](https://github.com/Rdatatable/data.table/issues/2778), [3](https://github.com/Rdatatable/data.table/issues/523), [4](https://github.com/Rdatatable/data.table/issues/971), [5](https://github.com/Rdatatable/data.table/issues/1197), [6](https://github.com/Rdatatable/data.table/issues/1414)
_NB_: `.SD[1L]` is currently optimized by [_`GForce`_](https://Rdatatable.gitlab.io/data.table/library/data.table/html/datatable-optimize.html) ([see also](https://stackoverflow.com/questions/22137591/about-gforce-in-data-table-1-9-2)), `data.table` internals which massively speed up the most common grouped operations like `sum` or `mean` -- see `?GForce` for more details and keep an eye on/voice support for feature improvement requests for updates on this front: [1](https://github.com/Rdatatable/data.table/issues/735), [2](https://github.com/Rdatatable/data.table/issues/2778), [3](https://github.com/Rdatatable/data.table/issues/523), [4](https://github.com/Rdatatable/data.table/issues/971), [5](https://github.com/Rdatatable/data.table/issues/1197), [6](https://github.com/Rdatatable/data.table/issues/1414)

## Grouped Regression

Expand Down