title: Python pandas: "Empty Dataframe" when selecting an interval of that Dataframe
body: <p>I am trying to select some rows between two dates inside a Dataframe. The problem is when I try, I get:</p>
  
  <blockquote>
    <p>Empty DataFrame</p>
  </blockquote>
  
  <p>I import some financial historical data and then puting the date column as the index (DatetimeIndex). </p>
  
  <p>When I try to individually select one row with a date, it works. It's when I try with a date interval that it doesn't (even if I checked each row individually).</p>
  
  <p>I tried to fill possible empty cells with <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.fillna.html" rel="nofollow">fillna()</a>, without success.</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  
  from datetime import datetime
  
  #Open Euro Euro Stoxx 50 csv file, rename columns and set dates as index
  
  euro_stoxx_50 = pd.read_csv('STOXX50E.csv', parse_dates = True, index_col = 0)
  euro_stoxx_50.columns = ['open', 'high', 'low', 'close', 'volume', 'adj close']
  euro_stoxx_50.index.names = ['date']
  </code></pre>
  
  <p>My problem with examples: </p>
  
  <pre><code>print euro_stoxx_50.head() 
  print euro_stoxx_50.index
  print euro_stoxx_50.empty
  print euro_stoxx_50['2012':'2015'].empty
  </code></pre>
  
  <p>Will give:</p>
  
  <pre><code>date         open     high      low    close    volume  adj close                                              
  2015-09-25  3113.16  3113.16  3113.16  3113.16       0    3113.16
  2015-09-24  3019.34  3019.34  3019.34  3019.34       0    3019.34
  2015-09-23  3079.99  3079.99  3079.99  3079.99       0    3079.99
  2015-09-22  3076.05  3076.05  3076.05  3076.05       0    3076.05
  2015-09-21  3184.72  3184.72  3184.72  3184.72       0    3184.72
  
  &lt;class 'pandas.tseries.index.DatetimeIndex'&gt;
  [2015-09-25, ..., 1986-12-31]
  Length: 7396, Freq: None, Timezone: None
  
  False
  
  True
  </code></pre>
  
  <p>And</p>
  
  <pre><code>print euro_stoxx_50['2012-9-12']
  print euro_stoxx_50['2012-9-13']
  print euro_stoxx_50['2012-9-12':'2012-9-13']
  </code></pre>
  
  <p>will give:</p>
  
  <pre><code>date        open    high     low   close  volume  adj close                                                        
  2012-09-12  2564.8  2564.8  2564.8  2564.8       0     2564.8
  
  
  date   open     high      low    close  volume  adj close                                                          
  2012-09-13  2543.22  2543.22  2543.22  2543.22       0    2543.22
  
  Empty DataFrame
  Columns: [open, high, low, close, volume, adj close]
  Index: []
  </code></pre>
  
  <p>edit     </p>
  
  <p>Thanks for any help!               </p>