<p>我认为最好使用<code>dict</code>来用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.Series.to_dict.html" rel="nofollow noreferrer">^{<cd2>}</a>保存数据:</p>
<pre><code>df = pd.DataFrame({'A':[1,2,3],
'B':[4,5,6],
'C':[7,8,9],
'D':[1,3,5],
'E':[5,3,6],
'F':[7,4,3]})
print (df)
A B C D E F
0 1 4 7 1 5 7
1 2 5 8 3 3 4
2 3 6 9 5 6 3
#select some row - e.g. with index 2
print (df.loc[2])
A 3
B 6
C 9
D 5
E 6
F 3
Name: 2, dtype: int64
d = df.loc[2].to_dict()
print (d)
{'E': 6, 'B': 6, 'F': 3, 'A': 3, 'C': 9, 'D': 5}
print (d['A'])
3
</code></pre>
<p>如果排序很重要,请使用<a href="https://docs.python.org/2/library/collections.html#collections.OrderedDict" rel="nofollow noreferrer">^{<cd3>}</a>:</p>
^{pr2}$
<p>如果需要列中的所有值,请使用<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.to_dict.html" rel="nofollow noreferrer">^{<cd4>}</a>:</p>
^{3}$
<hr/>
<pre><code>d = df.to_dict(orient='index')
print (d)
{0: {'E': 5, 'B': 4, 'F': 7, 'A': 1, 'C': 7, 'D': 1},
1: {'E': 3, 'B': 5, 'F': 4, 'A': 2, 'C': 8, 'D': 3},
2: {'E': 6, 'B': 6, 'F': 3, 'A': 3, 'C': 9, 'D': 5}}
#get value in row 2 and column A
print (d[2]['A'])
3
</code></pre>