Removal of strings after a term and not before-CodePudding

I'm looking at removing specific terms before certain words in a dataframe column.

data = {'Code':['001', '002', '003', '004', '005', '006','007'],
        'Territory':['Kinshasa West', 'West Kivu', 'East Tamaki', 'Sydney North','Sydney South','Brisbane East Suburb','Wattle Downs East']}
 
df = pd.DataFrame(data)
df

  Code             Territory
0  001         Kinshasa West
1  002             West Kivu
2  003           East Tamaki
3  004          Sydney North
4  005          Sydney South
5  006  Brisbane East Suburb
6  007     Wattle Downs East

I'm interested in removing words "West", "East", "North", "South" only if they are the last words in the column value. However, they should not be removed if they come before the last word.

Expected output:

  Code             Territory
0  001              Kinshasa
1  002             West Kivu
2  003           East Tamaki
3  004                Sydney
4  005                Sydney
5  006  Brisbane East Suburb
6  007          Wattle Downs

I'm able to filter out the specific terms from the column values but making use of word positions is the issue at the moment.

CodePudding user response：

You can use regex and .apply().

import re
def remove_nsew(territory):
    return re.sub(" (North|South|East|West)$", "", territory)
df["Territory"] = df["Territory"].apply(remove_nsew)

CodePudding user response：

Does the data start out as a list? You can use string manipulation on the list or convert it to a list and modify the dictionary

data = {'Code':['001', '002', '003', '004', '005', '006','007'],
        'Territory':['Kinshasa West', 'West Kivu', 'East Tamaki', 'Sydney North','Sydney South','Brisbane East Suburb','Wattle Downs East']}

list1 = list(data.values())

for index,value in enumerate(list1[1]):
    if(value.endswith("West")):
        list1[1][index] = value.replace("West", "")