pandas - Changing the format of a data frame
<p>I have a data frame which is of the format:</p>

<pre><code>level_0 level_1 counts
0   back    not_share   1183
1   back    share   1154
2   back    total   2337
3   front   not_share   697
4   front   share   1073
5   front   total   1770
6   left    not_share   4819
7   left    share   5097
8   left    total   9916
9   other   not_share   2649
10  other   share   2182
11  other   total   4831
12  right   not_share   1449
13  right   share   1744
14  right   total   3193
</code></pre>

<p>I want to convert this form to </p>

<pre><code>level_0 share not_share total
back    1154  1183      2337
front   1073  697       1770 
</code></pre>

<p>and so on..</p>

<p>Is there any method that I can use or should I convert it into a native Python datatype and then do the manipulations?</p>

<p>Use <code>groupby</code> and <code>sum</code></p>

<pre><code>df.groupby(['level_0', 'level_1']).counts.sum().unstack()
</code></pre>

<p><a href="http://i.stack.imgur.com/IeXuV.png"><img src="http://i.stack.imgur.com/IeXuV.png" alt="enter image description here"></a></p>

python pandas dataframe pivot