Replace values in data frame with Pandas

Question

I get this data frame:

               Item ................. 
0              Banana (From Spain)... 
1              Chocolate ............ 
2              Apple (From USA) ..... 
               ............

And I want change all Item's names by removing the parenthesis, getting finally

               Item ................. 
0              Banana ............... 
1              Chocolate ............ 
2              Apple ................ 
               ............

I thought, I should use replace but there are too much data so I'm thinking in use something like

import re

    for i in dataframe.index:
       if bool(re.search('.*\(.*\).*', dataframe.iloc[i]["Item"])):
          dataframe.ix[i,"Item"] = dataframe.iloc[i]["Item"].split(" (")[0]

But I'm not sure if is the most efficient way.

try this df.Item = df.Item.str.replace('\([^\)]*\)', '')

MaxU - stand with Ukraine
– MaxU - stand with Ukraine

2016-11-09 14:11:49 +00:00
Commented Nov 9, 2016 at 14:11 — MaxU - stand with Ukraine
– MaxU - stand with Ukraine, Commented Nov 9, 2016 at 14:11

Khris · Accepted Answer · 2016-11-09 14:18:08Z

2

This does the trick:

df.Item = df.Item.apply(lambda x: x.split(" (")[0])

answered Nov 9, 2016 at 14:18

Khris

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jezrael · Accepted Answer · 2016-11-09 14:16:42Z

2

You can use str.replace by regex with str.strip if need remove last whitespaces:

df.Item = df.Item.str.replace(r"\(.*\)","").str.strip()
print (df)
        Item
0     Banana
1  Chocolate
2      Apple

Another simplier solution with str.split with indexing with str:

df.Item = df.Item.str.split(' \(').str[0]
print (df)
        Item
0     Banana
1  Chocolate
2      Apple

answered Nov 9, 2016 at 14:16

jezrael

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