title: Convert irregular spaced data to timeseries
body: <p>I have a sales data over a period, I want to convert the data to time-series for time series related analysis. But I am stuck at the very first step, please suggest how to proceed. 
  Below is my transaction data, order_date, total_amount and Quantity. My order date is random( not evenly spaced).</p>
  
  <pre><code>&gt; sku_top_02
           ord_date total_amount qty
  36015  2014-01-02       379.81   1
  36022  2014-01-02       610.87   2
  36050  2014-01-03       289.17   6
  36081  2014-01-03       183.12   1
  36128  2014-01-06       303.57  10
  36193  2014-01-06        51.65   1
  36259  2014-01-07       250.31   1
  36222  2014-01-08       408.58   1
  36264  2014-01-09       183.40   1
  36347  2014-01-09       504.90   1
  36323  2014-01-13       529.95   1
  36412  2014-01-13       204.96   1
  36455  2014-01-14       524.83   5
  36504  2014-01-14      3771.41  25
  36762  2014-01-20       759.86   2
  36794  2014-01-21       539.88   2
  36826  2014-01-22       599.34   1
  37056  2014-01-22       133.35   3
  37076  2014-01-22       174.25   4
  ...
  ...
  ...
  Please ignore the first column (rownames, after sorting by order date it is jumbled). Below, I am using xts() to convert the data into time-series.
  
  &gt; ts.sku_02 &lt;- xts(df = sku_top_02[,c('total_amount', 'qty')], order.by = sku_top_02$ord_date)
  </code></pre>
  
  <p><strong>Something is not working in my conversion</strong></p>
  
  <pre><code>&gt; ts.sku_02
  Data:
  numeric(0)
  
  Index:
   Date[1:4386], format: "2014-01-02" "2014-01-02" "2014-01-03" "2014-01-03" "2014-01-06" "2014-01-06" "2014-01-07" "2014-01-08" "2014-01-09" "2014-01-09" ...
  &gt; dim(ts.sku_02)
  NULL
  &gt; str(ts.sku_02)
  An 'xts' object of zero-width
  </code></pre>
  
  <p>Also, I am not able to plot the TS. Please suggest how to proceed.
  Thanks in advance.</p>