这是我想出的。

代码：

import re
import pandas as pd
import numpy as np

# list of the strings we want to check for
check_strs = ['gross to net','gross up','net to gross','gross-to-net','gross-up','net-to-gross','gross 2 net','net 2 gross','gross net','net gross','memo code']

# From the re.escape() docs: Escape special characters in pattern. 
# This is useful if you want to match an arbitrary literal string that may have regular expression metacharacters in it.
check_strs_esc = [re.escape(curr_val) for curr_val in check_strs]

# join all the escaped strings as a single regex
check_strs_re = '|'.join(check_strs_esc)

test_col_1 = ['something with gross up.','without those words.',np.NaN,'or with Net to gross','if not then we give a "0"']
df_1 = pd.DataFrame(data=test_col_1,columns=['sr_description'])

df_1['contains_str'] = df_1['sr_description'].str.contains(check_strs_re,case=False,na=False)

print(df_1)

结果：

              sr_description  contains_str
0   something with gross up.          True
1       without those words.         False
2                        NaN         False
3       or with Net to gross          True
4  if not then we give a "0"         False

请注意，numpy并不是解决方案运行所必需的，我只是用它来测试NaN的值。

让我知道是否有任何不清楚的地方或您有任何疑问！ ：）