title: Plotting DataFrame with a datetime.time object problems
body: <p>I've started learning pandas for a few days now so that I can do a few analyzes of a big data set that I have received. </p>
  
  <p>My goal is: </p>
  
  <p><strong>1. To visualize the scan count per minute. (x=time, y=number of total scans)</strong></p>
  
  <p><strong>2. To visualize the scans per minute on a graph. (x=time, y=number of scans that minute)</strong></p>
  
  <p>If this is not clear enough let me know and I'll try my best to re-explain it.</p>
  
  <p>I created a new DataFrame consisting of 2 columns: Scan Type and Time</p>
  
  <pre><code>$ df.head()
  
               Scan Type      Time
  0  Mobile Multi Reject  13:32:00
  1  Mobile Multi Reject  13:33:00
  2  Mobile Multi Reject  13:33:00
  3       Barcode Reject  13:34:00
  4        Barcode Entry  13:34:00
  </code></pre>
  
  <p>The data types are as follows:</p>
  
  <pre><code>$ df.dtypes
  
  Scan Type    object
  Time         object
  dtype: object
  </code></pre>
  
  <p>My next step was to convert the Time object to datetime:</p>
  
  <pre><code>$ df['Time'] = pd.to_datetime(df['Time'], format='%H:%M:%S')
  
  $ df.dtypes
  
  Scan Type            object
  Time         datetime64[ns]
  dtype: object
  </code></pre>
  
  <p>Then I followed this answer <a href="https://stackoverflow.com/a/21333244/1067213">https://stackoverflow.com/a/21333244/1067213</a>  to present the data based on the count and got the following:</p>
  
  <p><a href="https://i.stack.imgur.com/2WAoX.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/2WAoX.png" alt="Scan Types based on Time"></a></p>
  
  <p><strong>Issue 1:</strong> The time is presented wrong and I don't understand what it uses as the time. The graph seems correct since the expected peak moments and scan flow matches with the expected one (through experience).</p>
  
  <p><strong>Issue 2:</strong> I could not manage to present the total scans based on the time.</p>
  
  <p>Thanks in advance, for more clarity or if you have any questions please leave a comment and I'll try my best to clarify or provide more information.</p>
  
  <p><strong><em>EDIT: This exactly the code I used to visualize the data:</em></strong></p>
  
  <pre><code>data = pd.read_excel("Scanlog.xlsx")
  df = pd.DataFrame(data, columns=['Scan Type', 'Time'])
  
  df['Time'] = pd.to_datetime(df['Time'], format="%H:%M:%S", errors="coerce")
  df.groupby([df['Time']]).count().plot(style=".", figsize=(15, 4))
  </code></pre>
  
  <p><strong>EDIT 2 - Solution for Issue 1:</strong>
  After some research I found that the missing part was the dt.time:</p>
  
  <pre><code>df['Time'] = pd.to_datetime(df['Time'], format="%H:%M:%S", errors="coerce").dt.time
  </code></pre>
  
  <p>Now the time is presented properly. </p>