擅长:python、mysql、java
<p>您可以使用参数<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.core.groupby.GroupBy.apply.html" rel="nofollow">^{<cd1>}</a><a href="http://docs.scipy.org/doc/numpy-1.10.1/reference/generated/numpy.unique.html" rel="nofollow">^{<cd2>}</a>使用参数<code>return_counts=True</code>:</p>
<pre><code>df = pd.DataFrame({'node':[1,2,3,3,3,5,5],'lang':['it','en','ar','ar','es','uz','es']})
print df
lang node
0 it 1
1 en 2
2 ar 3
3 ar 3
4 es 3
5 uz 5
6 es 5
a = df.groupby('node')['lang'].apply(lambda x: np.unique(x, return_counts=True))
.reset_index(name='tup')
#split tuples
a[['langs','lfreq']] = a['tup'].apply(pd.Series)
#filter columns
print a[['node','langs','lfreq']]
node langs lfreq
0 1 [it] [1]
1 2 [en] [1]
2 3 [ar, es] [2, 1]
3 5 [es, uz] [1, 1]
</code></pre>