您可以在两列上应用str.contains，然后使用any(axis=1)聚合布尔掩码：

words_of_interest = ["Space", "Aliens"]
pat = '|'.join(words_of_interest)
mask = df[['Title', 'Description']].apply(lambda x: x.str.contains(pat)).any(axis=1)

输出：

>>> df[mask]
        Title                                        Description
0     Area 51           Aliens come to earth on the 4th of July.
2  Spaceballs  A star-pilot for hire and his trusty sidekick ...

以下是其中一个选项：

m = df.stack().str.contains("|".join(words_of_interest)).unstack().any(axis=1)
​
out = df.loc[m]​

另一个使用re和 listcomp 的例子：

import re 

m = [bool(re.search("|".join(words_of_interest), str(v))) for v in df.to_numpy()]]

out = df.loc[m]

输出：

print(out)

        Title                                                  Description
0     Area 51                     Aliens come to earth on the 4th of July.
2  Spaceballs  A star-pilot for hire and his trusty sidekick must come ...