What is the meaning of "axis" attribute in a Pandas DataFrame?
<p>Taking the following example:</p>

<pre><code>&gt;&gt;&gt; df1 = pd.DataFrame({"x":[1, 2, 3, 4, 5], 
                        "y":[3, 4, 5, 6, 7]}, 
                      index=['a', 'b', 'c', 'd', 'e'])

&gt;&gt;&gt; df2 = pd.DataFrame({"y":[1, 3, 5, 7, 9], 
                        "z":[9, 8, 7, 6, 5]}, 
                      index=['b', 'c', 'd', 'e', 'f'])

&gt;&gt;&gt; pd.concat([df1, df2], join='inner')
</code></pre>

<p>The output is:</p>

<pre><code>   y
a  3
b  4
c  5
d  6
e  7
b  1
c  3
d  5
e  7
f  9
</code></pre>

<p>Since <code>axis=0</code> is the columns, I think tha <code>concat()</code> only considers <strong>columns</strong> that are found in both dataframes. But the acutal output considers <strong>rows</strong> that are found in both dataframes.</p>

<p>What is the exactly meaning of <code>axis</code> parameter?</p>