title: Problems getting data configured properly in an R tibble
body: <p>I have been struggling for some time to get my R tibble object in a state that I can use. Here is my current object.</p>
  
  <pre><code>str(myresults)
  Classes ‘tbl_time’, ‘tbl_df’, ‘tbl’ and 'data.frame':   433 obs. of  2 variables:
  $ DateTime  : POSIXct, format: "2018-07-28 21:00:00" "2018-07-28 22:00:00" ...
  $ ordercount: int  1 1 3 1 3 1 3 1 1 1 ...
     - attr(*, "index")= language ~DateTime     
     - attr(*, ".Environment")=&lt;environment: R_GlobalEnv&gt; 
     - attr(*, "time_zone")= chr ""
  </code></pre>
  
  <p>I then want to execute the following but get the error</p>
  
  <pre><code>myresults &lt;- myresults %&gt;% 
                  time_decompose(ordercount) %&gt;% 
                  anomalize(remainder) %&gt;% 
                  time_recompose()
  </code></pre>
  
  <blockquote>
    <p>Error: 'get_index_col' is not an exported object from 'namespace:tibbletime'</p>
  </blockquote>
  
  <p>I am reading my data from SQL Server, which automatically creates a data frame. Then I have to manipulate the data frame to get it into a state that that can handle the last command above (i.e. convert the factor to date + convert data frame to a tibble).</p>
  
  <p>If I read the data straight from a csv file it goes straight into a tibble and the command executes perfectly.</p>
  
  <p>I've tried so many different ways / functions to get this to work but getting to the point where I have nothing else to try.</p>
  
  <p>I'm sure there's something simple out there that will help but I'm fairly new to R.</p>
  
  <p>Can anyone point me in the right direction? I have included the code and data below.</p>
  
  <pre><code>    library(tidyverse)
      library(anomalize)
      library(RODBC)
  
      dbhandle &lt;- odbcDriverConnect('driver={SQL         Server};server=gbuksvr1.ktest.com;database=myDB;trusted_connection=true')
  
      myresults &lt;- sqlQuery(dbhandle, "select convert(varchar(30), [date]) + ' ' + [hour] as DateTime, ordercount from my_anomaly_data where site = 'keysite' and paymenttype = 'cash' order by datetime")
  
      myresults$DateTime &lt;- as.POSIXct(strptime(x = as.character(myresults$DateTime), format = "%Y-%m-%d %H:%M"))
  
      myresults &lt;- as_tbl_time(myresults, DateTime)
  
      myresults &lt;- myresults %&gt;% time_decompose(ordercount) %&gt;% anomalize(remainder) %&gt;% time_recompose()
  </code></pre>
  
  <p>And the data (an extract of it)...</p>
  
  <p>datetime,ordercount<br>
  2018-07-28 21:00,1<br>
  2018-07-28 22:00,1<br>
  2018-07-28 22:00,3<br>
  2018-07-29 00:00,1<br>
  2018-07-29 03:00,3<br>
  2018-07-29 04:00,1<br>
  2018-07-29 05:00,3<br>
  2018-07-29 07:00,1<br>
  2018-07-29 08:00,1<br>
  2018-07-29 08:00,1<br>
  2018-07-29 09:00,1<br>
  2018-07-29 09:00,3<br>
  2018-07-29 11:00,3<br>
  2018-07-29 13:00,4<br>
  2018-07-29 14:00,1<br>
  2018-07-29 14:00,1<br>
  2018-07-29 14:00,4<br>
  2018-07-29 15:00,2<br>
  2018-07-29 16:00,4<br>
  2018-07-29 16:00,1<br>
  2018-07-29 17:00,1<br>
  2018-07-29 17:00,2<br>
  2018-07-29 18:00,1<br>
  2018-07-29 18:00,4<br>
  2018-07-29 19:00,5<br>
  2018-07-29 20:00,2<br>
  2018-07-29 20:00,7<br>
  2018-07-29 21:00,1  </p>