由于\u200d不是可打印字符，因此以下是删除它并转换为整数的解决方案：

df = pd.DataFrame({'now_prices_after_fillna':['1450', u'\u200d1500']})
    
print (df)
  now_prices_after_fillna
0                    1450
1                   ‍1500

#https://stackoverflow.com/a/54451873/2901002
import sys

# build a table mapping all non-printable characters to None
NOPRINT_TRANS_TABLE = {
    i: None for i in range(0, sys.maxunicode + 1) if not chr(i).isprintable()
}

def make_printable(s):
    """Replace non-printable characters in a string."""

    # the translate method on str removes characters
    # that map to None from the string
    return s.translate(NOPRINT_TRANS_TABLE)

df['now_prices_after_fillna'] = (df['now_prices_after_fillna'].apply(make_printable)
                                                              .astype(int))
print (df)
   now_prices_after_fillna
0                     1450
1                     1500

另一个想法是，如果混合数字与字符串值添加try与except语句：

df = pd.DataFrame({'now_prices_after_fillna':['1450', u'\u200d1500', 1000]})
    
print (df)

#https://stackoverflow.com/a/54451873/2901002
import sys

# build a table mapping all non-printable characters to None
NOPRINT_TRANS_TABLE = {
    i: None for i in range(0, sys.maxunicode + 1) if not chr(i).isprintable()
}

def make_printable(s):
    """Replace non-printable characters in a string."""

    # the translate method on str removes characters
    # that map to None from the string
    try:
        return s.translate(NOPRINT_TRANS_TABLE)
    except AttributeError:
        return s

df['now_prices_after_fillna'] = (df['now_prices_after_fillna'].apply(make_printable)
                                                              .astype(int))
print (df)
   now_prices_after_fillna
0                     1450
1                     1500
2                     1000

测试您的真实的数据：
一个二个一个一个