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    <p>I think it is documented and consistent behaviour. </p> <p>The main thing to note is that the prefix <code>!</code> within the <code>i</code> argument is a flag for a not join, so <code>x != 0</code> and <code>!(x==0)</code> are no longer the same logical operation <strong>when working with the documented handling of NA within data.table</strong></p> <p>The section from the news regarding the <code>not join</code></p> <pre><code>A new "!" prefix on i signals 'not-join' (a.k.a. 'not-where'), #1384i. DT[-DT["a", which=TRUE, nomatch=0]] # old not-join idiom, still works DT[!"a"] # same result, now preferred. DT[!J(6),...] # !J == not-join DT[!2:3,...] # ! on all types of i DT[colA!=6L | colB!=23L,...] # multiple vector scanning approach (slow) DT[!J(6L,23L)] # same result, faster binary search '!' has been used rather than '-' : * to match the 'not-join'/'not-where' nomenclature * with '-', DT[-0] would return DT rather than DT[0] and not be backwards compatible. With '!', DT[!0] returns DT both before (since !0 is TRUE in base R) and after this new feature. * to leave DT[+J...] and DT[-J...] available for future use </code></pre> <p>And from <code>?data.table</code></p> <blockquote> <p>All types of 'i' may be prefixed with !. This signals a not-join or not-select should be performed. Throughout data.table documentation, where we refer to the type of 'i', we mean the type of 'i' after the '!', if present. See examples.</p> </blockquote> <hr> <p>Why is it consistent with the documented handling of NA within data.table</p> <p><code>NA</code> values are considered FALSE. Think of it like doing <code>isTRUE</code> on each element. </p> <p>so <code>DT[x!=0]</code> is indexed with <code>TRUE FALSE NA</code> which becomes <code>TRUE FALSE FALSE</code> due to the documented NA handling. </p> <p>You are wanting to subset when things are TRUE.</p> <p>This means you are getting those where x != 0 is TRUE ( and not NA)</p> <p><code>DT[!(x==0)]</code> uses the <strong>not join</strong> states you want everything that is not 0 (which can and will include the <code>NA</code> values). </p> <hr> <h2>follow up queries / further examples</h2> <h3><code>DT[!(x!=0)]</code></h3> <pre><code>## returns x y 1: 0 2 2: NA 3 </code></pre> <p><code>x!=0</code> is TRUE for one value, so the not join will return what isn't true. (ie what was <code>FALSE</code> (actually <code>== 0</code>) or <code>NA</code> </p> <h2><code>DT[!!(x==0)]</code></h2> <pre><code>## returns x y 1: 0 2 2: NA 3 </code></pre> <p>This is parsed as <code>!(!(x==0))</code>. The prefix <code>!</code> denotes a not join, and the inner <code>!(x==0)</code> is parsed identically to <code>x!=0</code>, so the reasoning from the case immediately above applies.</p>
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    1. COmnel, thanks for the wonderful explanation. As much as I find difficult to wrap my head around the fact that `!(x==.)` and `x != .` aren't equivalent (especially without a `J` present, I assumed a not-join is `!J(.)`), your explanation makes much sense to me. One more question. So with this behaviour, what would you expect the output for `DT[!!(x==0)]` should be and is it the same as the expected behaviour?
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    2. COBasically, it'd be great if you could clarify how data.table interprets `DT[!(x!=0)]` and `DT[!!(x==0)]`. I've trouble interpreting it.
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    3. CO@Arun, hopefully that has cleared it up.
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