Groupby ID pandas
<p>I have a data like:</p>

<pre><code>ID,"address","used_at","active_seconds","pageviews"
4be390eefaf9a64e7cb52937c4a5c77a,"e1.ru",2014-09-30 18:14:58,57,4
4be390eefaf9a64e7cb52937c4a5c77a,"e1.ru",2014-09-30 20:11:15,1884,90
4be390eefaf9a64e7cb52937c4a5c77a,"e1.ru",2014-10-04 09:44:21,1146,6
4be390eefaf9a64e7cb52937c4a5c77a,"avito.ru",2014-09-29 21:01:29,48,3
</code></pre>

<p>I have only date with <code>2014</code> and <code>2015</code> year.</p>

<p>I want to group by <code>address</code> and get the number of users to every year to every website, but I have an error</p>

<pre><code>print(DataFrame({'count' : infile.groupby(["address", infile['used_at'].dt.year].ID.nunique())}))

AttributeError: 'list' object has no attribute 'ID'
</code></pre>

<p>I try to rename my column </p>

<pre><code>infile = pd.read_csv("avito_trend.csv", header=None, parse_dates=[2], low_memory=False, names=['user', 'address', 'date', 'duration', 'unknown'] )
</code></pre>

<p>But i have no result. Because last name isn't disappear.</p>

<p>How can I do this group?</p>