擅长:python、mysql、java
<p>您可以用<code>NaN</code>填充所需列中的其余单元格,但它们不会“空”。为此,请在两个索引上使用<code>pd.merge</code>:</p>
<p><strong>设置</strong></p>
<pre><code>import pandas as pd
import numpy as np
df = pd.DataFrame({
'Actual': [18.442, 15.4233, 20.6217, 16.7, 18.185],
'Forecasted': [19.6377, 13.1665, 19.3992, 17.4557, 14.0053]
})
arr = np.zeros(3)
df_arr = pd.DataFrame({'Predictors': [arr]})
</code></pre>
<p><strong>合并df和df_arr</strong></p>
^{pr2}$
<p><strong>结果</strong></p>
<pre><code>>>> print(result)
Actual Forecasted Predictors
0 18.4420 19.6377 [0.0, 0.0, 0.0]
1 15.4233 13.1665 NaN
2 20.6217 19.3992 NaN
3 16.7000 17.4557 NaN
4 18.1850 14.0053 NaN
>>> result.loc[0, 'Predictors']
array([0., 0., 0.])
>>> result.loc[1, 'Predictors'] # actually contains a NaN value
nan
</code></pre>