擅长:python、mysql、java
<p>您可以使用<code>pandas.drop</code>排除这些列:</p>
<pre><code>all_data = all_data.drop(categorical_features, axis = 1)
</code></pre>
<p>将以下示例作为测试:</p>
<pre><code>import pandas as pd
import numpy as np
dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6, 4), index = dates, columns = list('ABCD'))
print(df)
features = ['B', 'D']
df = df.drop(features, axis = 1)
print(df)
</code></pre>
<p>输出:</p>
<pre><code> A B C D
2013-01-01 1.365473 -0.445448 0.244377 0.416889
2013-01-02 -0.307532 0.095569 1.356229 -0.306618
2013-01-03 0.971216 1.100189 0.932189 0.808151
2013-01-04 -0.030160 -0.796742 -0.383336 -0.409233
2013-01-05 0.006601 0.093678 -1.013768 1.439921
2013-01-06 0.560771 -0.452491 1.050500 -1.545958
A C
2013-01-01 1.365473 0.244377
2013-01-02 -0.307532 1.356229
2013-01-03 0.971216 0.932189
2013-01-04 -0.030160 -0.383336
2013-01-05 0.006601 -1.013768
2013-01-06 0.560771 1.050500
</code></pre>