title: ValueError with a rolling window max in a padas time series with list comprehension
body: <p>I have two years worth of sensor data in a pandas dataframe, interval is 1 minute.  The index is a time series. Looks like this:</p>
  <pre><code>
                       temp1     overtemp  time_to_overtemp
  datetime                                                    
  2019-01-02 09:31:00  305.96
  2019-01-02 09:32:00  305.98
  2019-01-02 09:33:00  305.70
  2019-01-02 09:34:00  305.30
  2019-01-02 09:35:00  306.88
  </code></pre>
  <p>My goal is to set overtemp = 1 if the temperature increases by 2% in the next 2 weeks and a 0 if it does not.  I then want to populate the time_to_overtemp with the time-delay to the maximum of that two week temperature.</p>
  <p>I had another thread recommend a solution that used .apply(), but it was slow.  I wanted to implement a list comprehension to speed things up.</p>
  <p>This is what I am working with right now:</p>
  <pre><code>df['overtemp'] = [1 if i*1.02 &lt;= df['temp1'].rolling('14D').max() else 0 for i in df['temp1']]
  </code></pre>
  <p>I have gotten this to work with other logic, but when I add the &lt;= logic I get a value error:</p>
  <pre><code>The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().
  </code></pre>
  <p>Also, I think the rolling window is looking backwards by default?  How can I get it looking forwards?</p>