Why does referencing a concatenated pandas dataframe return multiple entries?
<p>When I create a dataframe using concat like this:</p>

<pre><code>import pandas as pd
dfa = pd.DataFrame({'a':[1],'b':[2]})
dfb = pd.DataFrame({'a':[3],'b':[4]})
dfc = pd.concat([dfa,dfb])
</code></pre>

<p>And I try to reference like I would for any other DataFrame I get the following result:</p>

<pre><code>&gt;&gt;&gt; dfc['a'][0]
0    1
0    3
Name: a, dtype: int64
</code></pre>

<p>I would expect my concatenated DataFrame to behave like a normal DataFrame and return the integer that I want like this simple DataFrame does:</p>

<pre><code>&gt;&gt;&gt; dfa['a'][0]
1
</code></pre>

<p>I am just a beginner, is there a simple explanation for why the same call is returning an entire DataFrame and not the single entry that I want? Or, even better, an easy way to get my concatenated DataFrame to respond like a normal DataFrame when I try to reference it? Or should I be using something other than concat?</p>

<p><strong>EDITED</strong> (thx <a href="http://stackoverflow.com/users/2336654/pirsquared">piRSquared</a>'s comment)</p>

<p>Use <code>append()</code> instead <code>pd.concat()</code>:</p>

<pre><code>dfc = dfa.append(dfb, ignore_index=True)
dfc['a'][0]
1
</code></pre>

python pandas concat