<p dir="auto">See below for discussion</p>
<hr>
<div class="snippet-clipboard-content notranslate position-relative overflow-auto" data-snippet-clipboard-copy-content="In [19]: import pandas as pd

In [20]: import numpy as np

In [21]: import random

In [22]: df = pd.DataFrame(np.random.random_sample((20,5)), index=[random.choice('ABCDE') for x in range(20)])

In [23]: df.loc[:,0].ix['A'].median()
Out[23]: 0.57704085832236685

In [24]: pd.version.version
Out[24]: '0.12.0'


In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: import random

In [4]: df = pd.DataFrame(np.random.random_sample((20,5)), index=[random.choice('ABCDE') for x in range(20)])

In [5]: df.loc[:,0].ix['A'].median()
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
&lt;ipython-input-5-57f9fc9d1583&gt; in &lt;module&gt;()
----&gt; 1 df.loc[:,0].ix['A'].median()

AttributeError: 'numpy.ndarray' object has no attribute 'median'

In [6]: pd.version.version
Out[6]: '0.13.0rc1-43-g4f9fefc'"><pre class="notranslate"><code class="notranslate">In [19]: import pandas as pd

In [20]: import numpy as np

In [21]: import random

In [22]: df = pd.DataFrame(np.random.random_sample((20,5)), index=[random.choice('ABCDE') for x in range(20)])

In [23]: df.loc[:,0].ix['A'].median()
Out[23]: 0.57704085832236685

In [24]: pd.version.version
Out[24]: '0.12.0'


In [1]: import pandas as pd

In [2]: import numpy as np

In [3]: import random

In [4]: df = pd.DataFrame(np.random.random_sample((20,5)), index=[random.choice('ABCDE') for x in range(20)])

In [5]: df.loc[:,0].ix['A'].median()
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
&lt;ipython-input-5-57f9fc9d1583&gt; in &lt;module&gt;()
----&gt; 1 df.loc[:,0].ix['A'].median()

AttributeError: 'numpy.ndarray' object has no attribute 'median'

In [6]: pd.version.version
Out[6]: '0.13.0rc1-43-g4f9fefc'
</code></pre></div>
<p dir="auto">There is an issue with concat:<br>
I expect it not to  add rows from a second df in case there are such indexes in a first one.<br>
But this doesn't work for me. After a lot of search I found that this is because I have duplicate values in indexes in both df.<br>
It would be great to warn about such a behavior in standard function documentation.</p>
<p dir="auto">That is how I found that it is not a bug, but rather a feature:<br>
<a href="https://stackoverflow.com/questions/24089922/merge-multiple-dataframes-with-non-unique-indices/24091063#24091063" rel="nofollow">https://stackoverflow.com/questions/24089922/merge-multiple-dataframes-with-non-unique-indices/24091063#24091063</a></p>
<p dir="auto">Frankly speaking, I would prefer if there was an option to leave only "unique" indexes and in case they are present in first df - skip them all together during the concat</p>