<p>我看到许多张贴到StackOverflow的数据帧如下所示:</p>
<pre><code> a dt b
0 -0.713356 2015-10-01 00:00:00 -0.159170
1 -1.636397 2015-10-01 00:30:00 -1.038110
2 -1.390117 2015-10-01 01:00:00 -1.124016
</code></pre>
<p>我仍然没有找到一个好方法,可以使用<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_clipboard.html" rel="nofollow noreferrer">^{<cd1>}</a>(在<a href="https://pandas.pydata.org/pandas-docs/stable/generated/pandas.read_table.html#pandas.read_table" rel="nofollow noreferrer">^{<cd2>} docs</a>中的参数列表)将它们复制到我的解释器中</p>
<p>我认为关键是<code>parse_dates</code>参数:</p>
<pre><code>parse_dates : boolean or list of ints or names or list of lists or dict, default False
* boolean. If True -> try parsing the index.
* list of ints or names. e.g. If [1, 2, 3] -> try parsing columns 1, 2, 3 each as a separate date column.
* list of lists. e.g. If [[1, 3]] -> combine columns 1 and 3 and parse as a single date column.
* dict, e.g. {‘foo’ : [1, 3]} -> parse columns 1, 3 as date and call result ‘foo’
</code></pre>
<p><code>pd.read_clipboard(parse_dates={'dt': [1, 2]})</code>引发异常<code>NotImplementedError: file structure not yet supported</code></p>
<p>当我尝试跳过第一行<code>pd.read_clipboard(parse_dates=[[1, 2]], names=['a', 'dt1', 'dt2', 'b'], skiprows=1, header=None)</code>时,我得到了相同的异常</p>
<p>其他人是如何做到这一点的</p>