I have data as below:

I want to mask this data as below one


So I tried below code :

 readFile = pd.read_csv("C:/Users/siddhesh.kalgaonkar/Desktop/data01.txt",header=None)
 readFile.columns = ['IP']
 readFile['IP']=readFile['IP'].str.replace("(?<! )","X").astype('str')

but I gives me data as below one which is not correct:


I am new to pandas. So where am I going wrong ?

Also, I want to do it without pandas because the platform on which I would be deploying this code may be won't have pandas. So need to be ready for the other scenario as well. Below is my code:

 finalValues = re.sub("(?<! ).","X",readFiles)  

It gives below error:

>>> finalValues = re.sub("(?<! ).","X",readFiles)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Users\siddhesh.kalgaonkar\AppData\Local\Programs\Python\Python36\lib\re.py", line 191, in sub
    return _compile(pattern, flags).sub(repl, string, count)
TypeError: expected string or bytes-like object

I want to split this data on the basis of delimiter (in case I have multiple columns) and then I have to apply regex logic. Please help me out here.

  • $\begingroup$ What is not correct with the readFile dataframe generated from the pd.read_csv call? Whats wrong about it? $\endgroup$ – yoav_aaa Apr 11 '19 at 10:04
  • $\begingroup$ I have modified my question. Thanks for pointing out $\endgroup$ – Debuggerrr Apr 11 '19 at 10:07
  • $\begingroup$ So your problem is the code replacing the '.' into X? $\endgroup$ – yoav_aaa Apr 11 '19 at 10:15
  • $\begingroup$ Everything into X except first digit and '.' $\endgroup$ – Debuggerrr Apr 11 '19 at 10:16

Try this if you decide to use pandas:

readFile = pd.read_csv("C:/Users/siddhesh.kalgaonkar/Desktop/data01.txt",header=None)
readFile.columns = ['IP']
readFile['IP'] = readFile['IP'].replace(regex='((?<=[0-9])[0-9]|(?<=\.)[0-9])',value='X')

and this without pandas:

readFile = open("C:/Users/siddhesh.kalgaonkar/Desktop/data01.txt","r")
for line in readFile:
    lines = line.strip()
    finalline = re.sub(pattern='((?<=[0-9])[0-9]|(?<=\.)[0-9])',repl='X',string=lines)

(?<=[0-9])[0-9] this part matches if the current position in the string is a digit and is preceded by a digit.

| or

(?<=\.)[0-9]) this part matches if the current position in the string is is a digit and is preceded by a period.

| improve this answer | |
  • $\begingroup$ But what if I have multiple columns and I want to use delimiter to separate columns and then apply the logic. Can you modify your answer using without pandas.Using pandas I know how to do it $\endgroup$ – Debuggerrr Apr 11 '19 at 12:36

This is pure(almost) python:

list(map(lambda x: x[0] + '.'.join(['X' * len(c) for c in x[1:].split('.')]), my_df['IP']))

- Use the map to iterate over each row in my_df['IP'] column.
- Per each IP value, split into first char and others using the x[0], x[1:]
- Get each part in x[1:] using the split method.
- For each part get its length and accordingly create a string made of X's.
- Rejoin this X's string into one string with '.' between them.

If using python2 you dont need the list.

| improve this answer | |
  • $\begingroup$ Yeah, it worked can you just explain join method in detail. Also, why do we need list over here $\endgroup$ – Debuggerrr Apr 11 '19 at 10:51

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