title: how to convert a very large dataset to xts? - as.xts fails on 1.5M rows
body: <p>I have the data:</p>
  
  <pre><code>dput(head(data))
  
  &gt; dput(head(data))
  structure(list(Gmt.time = c("01.06.2015 00:00", "01.06.2015 00:01", 
  "01.06.2015 00:02", "01.06.2015 00:03", "01.06.2015 00:04", "01.06.2015 00:05"
  ), Open = c(0.88312, 0.88337, 0.88377, 0.88412, 0.88393, 0.8838
  ), High = c(0.88337, 0.88378, 0.88418, 0.88418, 0.88393, 0.88393
  ), Low = c(0.883, 0.88337, 0.88374, 0.88394, 0.88368, 0.88362
  ), Close = c(0.88337, 0.88375, 0.88412, 0.88394, 0.8838, 0.88393
  ), Volume = c(83.27, 100.14, 117.18, 52.53, 77.69, 91.63)), .Names = c("Gmt.time", 
  "Open", "High", "Low", "Close", "Volume"), row.names = c(NA, 
  6L), class = "data.frame")
  &gt; 
  </code></pre>
  
  <p>and no NA values</p>
  
  <pre><code>any(is.na(head(data)))
  [1] FALSE
  </code></pre>
  
  <p>if i run this on the first few elements as in the data provided: </p>
  
  <pre><code>data_xts &lt;- xts(head(data[,2:6]), as.POSIXct(head(data[,1]), format='%d.%m.%Y %H:%M'))
  </code></pre>
  
  <p>it works fine</p>
  
  <p>but if i run on full dataset </p>
  
  <pre><code>&gt; nrow(data)
  [1] 1581120
  </code></pre>
  
  <p>i get:</p>
  
  <pre><code>&gt; data_xts &lt;- xts(data[,2:6], as.POSIXct(data[,1], format='%d.%m.%Y %H:%M'))
  Error in xts(data[, 2:6], as.POSIXct(data[, 1], format = "%d.%m.%Y %H:%M")) : 
    'order.by' cannot contain 'NA', 'NaN', or 'Inf'
  </code></pre>