Remove certain characters if on end of string in Pandas

Question

I have a list of names in which I have made all uppercase, removed spaces, and non-alphabetic characters to more easily merge with another list -- both are in pandas dataframe.

One of the dataframe's names have some names with JR attached to the end while their counterparts in the other dataframe to not contain this suffix. How can I strip all JR from both?

I tried something like the following:

df['NAME'] = df['NAME'].str.replace('JR','')

but I think this would remove all instances of JR and not when it is the last 2 characters. Any help would be appreciated.

Answer 1

You could use replace with a regex:

import pandas as pd

df = pd.DataFrame(data=['Name JR', 'Name JR Middle', 'JR Name'], columns=['name'])
df['name'] = df.name.str.replace(r'\bJR$', '', regex=True).str.strip()

print(df)

Output

             name
0            Name
1  Name JR Middle
2         JR Name

The pattern '\bJR$' matches the word JR only at the end of the string.

Answer 2

You need:

def jr_replace(x):
    match = re.sub(r'JR$',"",x)
    return match

df['NAME'] = df['NAME'].apply(jr_replace)

print(df)

Answer 3

One option is to remove JR using string.endswith, and remove it from the rows that contain it sclicing the str object:

m = s.str.endswith('JR')
s.loc[m] = s.loc[m].str[:-2]

---

Example

Using @danielmesejo's dataframe:

df = pd.DataFrame(data=['Name JR', 'Name JR Middle', 'JR Name'], columns=['name'])
m = df.name.str.endswith('JR')
df.name.loc[m] =  df.name.loc[m].str[:-2]

            name
0           Name 
1  Name JR Middle
2         JR Name