在 Python 中用 "N/A" 替换特殊字符

Question

我想将所有只有表情符号的行（例如 df['Comments'][2] 更改为 N/A。

df['Comments'][:6]
0                                                          nice
1                                                       Insane3
2                                                          ❤️
3                                                @bertelsen1986
4                       20 or 30 mm rise on the Renthal Fatbar?
5                                     Luckily I have one to

以下代码没有return我期望的输出：

df['Comments'].replace(';', ':', '!', '*', np.NaN)

预期输出：

df['Comments'][:6]
0                                                          nice
1                                                       Insane3
2                                                          nan
3                                                @bertelsen1986
4                       20 or 30 mm rise on the Renthal Fatbar?
5                                     Luckily I have one to

Answer 1

您可以通过遍历每行中的 unicode 字符（使用 emoji and unicodedata 包）来检测仅包含表情符号的行：

df = {}
df['Comments'] = ["Test", "Hello ", ""]

import unicodedata
import numpy as np
from emoji import UNICODE_EMOJI
for i in range(len(df['Comments'])):
    pure_emoji = True
    for unicode_char in unicodedata.normalize('NFC', df['Comments'][i]):
        if unicode_char not in UNICODE_EMOJI:
            pure_emoji = False
            break
    if pure_emoji:
        df['Comments'][i] = np.NaN
print(df['Comments'])

Answer 2

函数（remove_emoji）参考

尝试
先安装 emoji lib - pip install emoji

import re
import emoji

df.Comments.apply(lambda x: x if (re.sub(r'(:[!_\-\w]+:)', '', emoji.demojize(x)) != "") else np.nan)
0                         nice
1                      Insane3
2                          NaN
3               @bertelsen1986
4    Luckily I have one to 
Name: a, dtype: object

在 Python 中用 "N/A" 替换特殊字符

Replace special characters with "N/A" in Python

python

regex

special-characters

python-3.x

pandas