<p>对每个<code>reviewerName</code>的<code>dictionaries</code>使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html" rel="nofollow noreferrer">^{<cd1>}</a>和lambda函数,然后输出<code>Series</code>convert by <a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.to_dict.html" rel="nofollow noreferrer">^{<cd5>}</a>:</p>
<pre><code>print (df)
reviewerName title reviewerRatings
0 Charles Harry Potter Book Seven News:... 3.0
1 Charles Harry Potter Boxed Set, Books... 5.0
2 Charles Harry Potter and the Sorcerer... 5.0
3 Katherine Harry Potter and the Half-Blo... 5.0
4 Katherine Harry otter and the Order of... 5.0
</code></pre>
<hr/>
<pre><code>d = (df.groupby('reviewerName')['title','reviewerRatings']
.apply(lambda x: dict(x.values))
.to_dict())
print (d)
{
'Charles': {
'Harry Potter Book Seven News:...': 3.0,
'Harry Potter Boxed Set, Books...': 5.0,
'Harry Potter and the Sorcerer...': 5.0
},
'Katherine': {
'Harry Potter and the Half-Blo...': 5.0,
'Harry otter and the Order of...': 5.0
}
}
</code></pre>