根据正则表达式匹配替换整个字符串

Question

I have a large pandas dataframe of email address and wanted to replace all the .edu emails with "Edu". I came up with an highly inefficient way of doing it but there has to be a better way of doing it. This is how I do it:

import pandas as pd
import re
inp = [{'c1':10, 'c2':'gedua.com'},   {'c1':11,'c2':'wewewe.Edu'},   {'c1':12,'c2':'wewewe.edu.ney'}]
dfn = pd.DataFrame(inp)

for index, row in dfn.iterrows():
    try:
        if len(re.search('\.edu', row['c2']).group(0)) > 1:
            dfn.c2[index] = 'Edu'
            print('Education')
    except:
        continue

Answer 1

Using str.contains for case insensitive selection, and assignment with loc .

dfn.loc[dfn.c2.str.contains(r'\.Edu', case=False), 'c2'] = 'Edu'    
dfn

   c1         c2
0  10  gedua.com
1  11        Edu
2  12        Edu

If it's only the emails ending with .edu you want to replace, then

dfn.loc[dfn.c2.str.contains(r'\.Edu$', case=False), 'c2'] = 'Edu'

Or, as suggested by piR,

dfn.loc[dfn.c2.str.endswith('.Edu'), 'c2'] = 'Edu'

dfn

   c1              c2
0  10       gedua.com
1  11             Edu
2  12  wewewe.edu.ney  

Answer 2

replace

dfn.replace('^.*\.Edu$', 'Edu', regex=True)

   c1              c2
0  10       gedua.com
1  11             Edu
2  12  wewewe.edu.ney

The pattern '^.*\\.Edu$' says grab everything from the beginning of the string to the point where we find '.Edu' followed by the end of the string, then replace that whole thing with 'Edu'

---

Column specific

You may want to limit the scope to just a column (or columns). You can do that by passing a dictionary to replace where the outer key specifies the column and the dictionary value specifies what is to be replaced.

dfn.replace({'c2': {'^.*\.Edu$': 'Edu'}}, regex=True)

   c1              c2
0  10       gedua.com
1  11             Edu
2  12  wewewe.edu.ney

---

Case insensitive [ thx @coldspeed ]

pandas.DataFrame.replace does not have a case flag. But you can imbed it in the pattern with '(?i)'

dfn.replace({'c2': {'(?i)^.*\.edu$': 'Edu'}}, regex=True)

   c1              c2
0  10       gedua.com
1  11             Edu
2  12  wewewe.edu.ney