Given that this is the top Google result when searching for "Pandas replace is not working" I'd like to also mention that:

replace does full replacement searches, unless you turn on the regex switch. Use regex=True, and it should perform partial replacements as well.

This took me 30 minutes to find out, so hopefully I've saved the next person 30 minutes.

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')
print(readFile)

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)
    print(finalline)

(?<=[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.

It works if you escape the pipe.

>>> df[0].str.replace(" \| ", "@")
0    abc@def
Name: 0, dtype: object

The str.replace function is equivalent to re.sub:

import re

>>> re.sub(' | ', '@', "abc | def")
'abc@|@def'

>>> "abc | def".replace(' | ', '@')
'abc@def'

Series.str.replace(pat, repl, n=-1, case=True, flags=0): Replace occurrences of pattern/regex in the Series/Index with some other string. Equivalent to str.replace() or re.sub().

Here's a different syntax which I frequently use:

def supp_read(number):
    filename = f"supplemental-table{number}.xlsx"
    df = pd.read_excel(filename,skiprows=5)
    df.columns = df.columns.str.lower().replace(" ", "_")
    return df