Python 精确的单词匹配并在列中显示

我有以下数据帧（df）

还有列表中的一些单词，我需要搜索一个精确的匹配项

word_list = ['look','be','him']

这是我想要的输出

   Comments                       ID Word_01 Word_02 Word_03
0        10         Looking for help                        
1        11  Look at him but be nice    look     be      him
2        12                  Be calm    be                
3        13               Being good                        
4        14              Him and Her    him                
5        15                  Himself  

我试过一些方法，比如str.findall

str.findall(r"\b" + '|'.join(word_list) + r"\b",flags = re.I)

还有一些其他的，但我似乎无法得到我的话的精确匹配

如能帮助解决此问题，我们将不胜感激

---

谢谢

您可以使用pandas的

应用

功能。 例如：

产出：

   Comments                       ID
0        10         Looking for help
1        11  Look at him but be nice
2        12                  Be calm
3        13               Being good
4        14              Him and Her
5        15                  Himself

   Comments                       ID Word_0 Word_1 Word_2
0        10         Looking for help   look   None   None
1        11  Look at him but be nice   look     be    him
2        12                  Be calm   None     be   None
3        13               Being good   None     be   None
4        14              Him and Her   None   None    him
5        15                  Himself   None   None    him

---

每个单词都需要单词边界。一种可能的解决方案是使用原始的

数据帧

：

word_list = ['look','be','him']

pat = '|'.join(r"\b{}\b".format(x) for x in word_list)
df1 = df['ID'].str.extractall('(' + pat + ')', flags = re.I)[0].unstack().add_prefix('Word_')

对于输出中的小写数据，请添加：

---

您的解决方案应按相同的模式进行更改，将值转换为

列表

s和

连接

为原始值：

pat = '|'.join(r"\b{}\b".format(x) for x in word_list)
df1 = (pd.DataFrame(df['ID']
        .str.findall(pat, flags = re.I).values.tolist())
        .add_prefix('Word_')
        .fillna(''))   

或使用列表理解（应该是最快的）：

对于小写，添加

.lower（）

：

---

你说的“精确”匹配是什么意思？

str.findall

方法的哪部分结果不合适？这不是有效的Python。现在计算机上没有，很难找到正确的引号字符。如果不适合，请随意编辑我的帖子。太棒了。谢谢你的帮助

word_list = ['look','be','him']

pat = '|'.join(r"\b{}\b".format(x) for x in word_list)
df1 = df['ID'].str.extractall('(' + pat + ')', flags = re.I)[0].unstack().add_prefix('Word_')

df1 = (df['ID'].str.lower()
               .str.extractall('(' + pat + ')')[0]
               .unstack()
               .add_prefix('Word_'))

df = df.join(df1).fillna('')
print (df)
   Comments                       ID Word_0 Word_1 Word_2
0        10         Looking for help                     
1        11  Look at him but be nice   Look    him     be
2        12                  Be calm     Be              
3        13               Being good                     
4        14              Him and Her    Him              
5        15                  Himself              

pat = '|'.join(r"\b{}\b".format(x) for x in word_list)
df1 = (pd.DataFrame(df['ID']
        .str.findall(pat, flags = re.I).values.tolist())
        .add_prefix('Word_')
        .fillna(''))   

df1 = (pd.DataFrame([re.findall(pat, x, flags = re.I) for x in df['ID']])
       .add_prefix('Word_')
       .fillna(''))

pat = '|'.join(r"\b{}\b".format(x) for x in word_list)
df1 = (pd.DataFrame([re.findall(pat, x.lower(), flags = re.I) for x in df['ID']])
           .add_prefix('Word_')
           .fillna(''))