title: Aggregate columns with same date (sum)
body: <p>So, i need to aggregate rows where the date is the same.</p>
  
  <p>My code, as of now, returns the following:</p>
  
  <pre><code>                      date  value  source
  0  2018-04-08 15:52:26.110      1  ANAPRO
  1  2018-04-22 12:14:38.807      1  ANAPRO
  2  2018-04-22 12:34:18.403      1  ANAPRO
  3  2018-04-22 12:40:35.877      1  ANAPRO
  4  2018-04-22 12:53:57.897      1  ANAPRO
  5  2018-04-22 13:02:45.180      1  ANAPRO
  6  2018-05-04 17:41:15.840      1  ANAPRO
  7  2018-04-22 15:03:54.353      1  ANAPRO
  8  2018-04-22 15:24:27.030      1  ANAPRO
  9  2018-04-22 15:27:56.813      1  ANAPRO
  </code></pre>
  
  <p>I don't think I can aggregate the columns while I have HH:MM:SS.ms being showed alongside the date (I only need the date)</p>
  
  <p>I've tried this :</p>
  
  <pre><code>df['date'] = pandas.to_datetime(df['date'], format='%b %d %Y.%f').astype(str)
  </code></pre>
  
  <p>But to no avail, I still got the same return. </p>
  
  <p>The code is: </p>
  
  <p>Reads the my excel file (user input).</p>
  
  <pre><code>df = pandas.read_excel(var + '.xlsx')
  </code></pre>
  
  <p>Selects the columns I need, and create a new .xlsx to contain it.</p>
  
  <pre><code>df = df.iloc[:, 36].to_excel(var + '_.xlsx', index=False)
  </code></pre>
  
  <p>Opens the new .xlsx file.</p>
  
  <pre><code>df = pandas.read_excel(var + '_.xlsx')
  </code></pre>
  
  <p>Renames the column</p>
  
  <pre><code>df = df.rename(columns={'Prospect Dt. Cadastro': 'date'})
  </code></pre>
  
  <p>Adds the other columns I need.</p>
  
  <pre><code>df['value'] = 1
  df['source'] = 'ANAPRO'
  </code></pre>
  
  <p>Tries to format the date.</p>
  
  <pre><code>df['date'] = pandas.to_datetime(df['date'], format='%b %d` %Y.%f').astype(str)
  </code></pre>
  
  <p>Creates the final xlsx, with all the formatted data.</p>
  
  <pre><code>df = df.to_excel('payload.xlsx')
  </code></pre>
  
  <p>Reads the final xlsx.</p>
  
  <pre><code>df = pandas.read_excel('payload.xlsx', names=['date', 'value', 'source'])
  </code></pre>
  
  <p>Prints the first 10 rows.</p>
  
  <pre><code>print(df.head(10))
  </code></pre>
  
  <p>I'm new to python, so sorry if I'm doing something awkward, thank you!</p>