在熊猫中使用正则表达式删除表情符号或替换文本答案

【问题标题】：Delete emojis or replace for text using regex in pandas在熊猫中使用正则表达式删除表情符号或替换文本
【发布时间】：2021-07-30 22:43:49
【问题描述】：

我有这个玩具数据集：

df = pd.DataFrame({'id':[1,2,3,4,5,6],
                   'text':['Oh no Monday','Oh no Monday','Gotcha ????????!',
                           'Coffee, please','Coffee, please','Mails ????'],
                   'dates':['2019-05-30T17:48:45+0000','2019-05-30T17:48:45+0000',
                           '2019-05-25T19:40:43+0000','2019-03-30T14:41:20+0000',
                           '2019-03-30T14:41:20+0000','2019-04-10T19:50:49+0000'],
                   'group':['meme','humour','meme','gif','gif','meme'],
                   'theme':['light','light','funny','dark','sad','funny']})

id  text    dates   group   theme
0   1   Oh no Monday    2019-05-30T17:48:45+0000    meme    light
1   2   Oh no Monday    2019-05-30T17:48:45+0000    humour  light
2   3   Gotcha ????????!    2019-05-25T19:40:43+0000    meme    funny
3   4   Coffee, please  2019-03-30T14:41:20+0000    gif dark
4   5   Coffee, please  2019-03-30T14:41:20+0000    gif sad
5   6   Mails ????    2019-04-10T19:50:49+0000    meme    funny

我想删除表情符号或将表情符号替换为文本。我试过这个：

df['clean_text'] = df['text'].str.extract(r'(^[a-zA-Z]+)')

但它会删除我较长的文本，例如我想要Oh no Monday，但我只得到Oh！：


id  text                dates                       group   theme   clean_text
0   1   Oh no Monday    2019-05-30T17:48:45+0000    meme    light   Oh
1   2   Oh no Monday    2019-05-30T17:48:45+0000    humour  light   Oh
2   3   Gotcha ????????!        2019-05-25T19:40:43+0000    meme    funny   Gotcha
3   4   Coffee, please  2019-03-30T14:41:20+0000    gif dark    Coffee
4   5   Coffee, please  2019-03-30T14:41:20+0000    gif sad Coffee
5   6   Mails ????        2019-04-10T19:50:49+0000    meme    funny   Mails

拜托，任何帮助或指导将不胜感激。

【问题讨论】：

df['clean_text'] = df['text'].str.replace(r'[^\w\s!\"£$%\^&\*()_+=\-\-\[\]}{#'';:@~/\.,<>\?\|]', '')
谢谢@MDR，直截了当的回答！

标签： python regex pandas

【解决方案1】：

您可以使用正则表达式删除表情符号：

pat = r'[\U0001F600-\U0001F64F]|[\U0001F300-\U0001F5FF]|[\U0001F680-\U0001F6FF]|[\U0001F1E0-\U0001F1FF]'

>>> df['text'].str.replace(pat, '', regex=True)
0      Oh no Monday
1      Oh no Monday
2          Gotcha !
3    Coffee, please
4    Coffee, please
5            Mails
Name: text, dtype: object

完整列表：

# https://en.wikipedia.org/wiki/Unicode_block
EMOJI_PATTERN = re.compile(
    "["
    "\U0001F1E0-\U0001F1FF"  # flags (iOS)
    "\U0001F300-\U0001F5FF"  # symbols & pictographs
    "\U0001F600-\U0001F64F"  # emoticons
    "\U0001F680-\U0001F6FF"  # transport & map symbols
    "\U0001F700-\U0001F77F"  # alchemical symbols
    "\U0001F780-\U0001F7FF"  # Geometric Shapes Extended
    "\U0001F800-\U0001F8FF"  # Supplemental Arrows-C
    "\U0001F900-\U0001F9FF"  # Supplemental Symbols and Pictographs
    "\U0001FA00-\U0001FA6F"  # Chess Symbols
    "\U0001FA70-\U0001FAFF"  # Symbols and Pictographs Extended-A
    "\U00002702-\U000027B0"  # Dingbats
    "\U000024C2-\U0001F251" 
    "]+"
)

df['text'].str.replace(EMOJI_PATTERN, '', regex=True)

【讨论】：

谢谢@Corralien，它工作正常！了解此类表情符号代码很有趣！