mjhjmtu

I have data frame in which txt column contains a list. I want to clean the txt column using function clean_text().

data = 'value':['abc.txt', 'cda.txt'], 'txt':['[''2019/01/31-11:56:23.288258 1886 7F0ED4CDC704 asfasnfs: remove datepart'']',
 '[''2019/02/01-11:56:23.288258 1886 7F0ED4CDC704 asfasnfs: remove datepart'']']
df = pandas.DataFrame(data=data)

def clean_text(text):
 """
 :param text: it is the plain text
 :return: cleaned text
 """
 patterns = [r"^53",
 r"[A-Za-z]+[d]+[w]*|[d]+[A-Za-z]+[w]*",
 r"[-=/':,?$[]-_()>.~" ";+]"]

 for p in patterns:
 text = re.sub(p, '', text)

 return text

My Solution:

df['txt'] = df['txt'].apply(lambda x: clean_text(x))

But I am getting below error:
Error

sre_constants.error: nothing to repeat at position 1

^53 is not a valid regular expression, since the repeater 53 must be preceded by a character or a pattern that can be repeated. If you mean to make it validate a string that is at least 53 characters long you can use the following pattern instead:

^.53

The culprit is the first pattern from the list - r"^53". It reads: ^ - match the beginning of the string and then 53 repeat the previous character or group 53 times. Wait... but there is no other character than ^ which cannot be repeated! Indeed. Add a char that you want to match 53 repetitions of. Or, escape the sequence 53 if you want to match it verbatim, e.g. using re.escape.