擅长:python、mysql、java
<p>这对我很有用:</p>
<pre><code>import numpy as np
arr1=[2019, 12, 17]
arr2=[12, 34, 17,
18, 17, 36,
15, 23, 40]
print(arr1,arr2)
</code></pre>
<p>输出:</p>
<pre><code>[2019, 12, 17] [12, 34, 17, 18, 17, 36, 15, 23, 40]
</code></pre>
<pre><code>arr2 = np.array(arr2).reshape((3,3))
arr1 = np.array([arr1,]*3)
newArray = np.hstack((arr1,arr2))
</code></pre>
<p>输出:</p>
<pre><code> array([[2019, 12, 17, 12, 34, 17],
[2019, 12, 17, 18, 17, 36],
[2019, 12, 17, 15, 23, 40]])
</code></pre>
<p><em>更新</em>,为了提高大型数据集的性能,只需在重新调整阵列形状后堆叠新值:</p>
<pre><code>arr1=[2019, 12, 17]
newEntry = [1,2,3]
nE = np.hstack((arr1,newEntry))
np.vstack((newArray,nE))
</code></pre>
<p>输出:</p>
<pre><code>array([[2019, 12, 17, 12, 34, 17],
[2019, 12, 17, 18, 17, 36],
[2019, 12, 17, 15, 23, 40],
[2019, 12, 17, 1, 2, 3]])
</code></pre>
<p><em>更新</em>在不了解exakt维度的情况下,您只需使用:</p>
<pre><code>np.arange(arr2).reshape(-1, 3)
</code></pre>