<p>您需要将<code>DataFrames</code>追加到列表<code>dfs</code>中,然后将<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.concat.html" rel="nofollow">^{<cd3>}</a>与参数<code>axis=1</code>一起使用:</p>
<pre><code>import pandas as pd
list111 = [ (72.0, 578.18, 378.0, 591.71),
(54.0, 564.18, 378.0, 577.71),
(54.0, 550.18, 378.0, 563.71),
(54.0, 536.18, 378.0, 549.71)]
dfs = []
list_title = ["x","y","h","w"]
for textbox in list111:
zipped=zip(list_title,textbox)
df1 = pd.DataFrame(zipped)
dfs.append(df1)
df = pd.concat(dfs, axis=1, ignore_index=True)
print df
0 1 2 3 4 5 6 7
0 x 72.00 x 54.00 x 54.00 x 54.00
1 y 578.18 y 564.18 y 550.18 y 536.18
2 h 378.00 h 378.00 h 378.00 h 378.00
3 w 591.71 w 577.71 w 563.71 w 549.71
</code></pre>
<p>如果需要一个公共列作为<code>index</code>:</p>
^{pr2}$
<p>但我认为最好是使用<code>DataFrame</code>构造函数和<a href="http://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.T.html" rel="nofollow">^{<cd7>}</a>:</p>
<pre><code>import pandas as pd
list111 = [ (72.0, 578.18, 378.0, 591.71),
(54.0, 564.18, 378.0, 577.71),
(54.0, 550.18, 378.0, 563.71),
(54.0, 536.18, 378.0, 549.71)]
list_title = ["x","y","h","w"]
print pd.DataFrame([li for li in list111], columns=list_title).T
0 1 2 3
x 72.00 54.00 54.00 54.00
y 578.18 564.18 550.18 536.18
h 378.00 378.00 378.00 378.00
w 591.71 577.71 563.71 549.71
</code></pre>