CODEWITHSUNDEEP
pythonpandasregexstring
James
James

Reputation: 538

keyword based extraction from text in pandas

I have a dataset having two columns:

Index            Text
 1               *some text* address13/b srs mall, indirapuram,sann-444000 *some text*
 2               *some text*   
 3               *some text* contactus 12J 1st floor, jajan,totl-996633 *some text*
 4               ..........
 5               ........

I want a dataframe having a new column as "location" where only that string will get extracted from column "Text" that is beyond the keywords "address" or "contactus" till the 6 digits number and gives "NA" where string not get matched. Output what I want is something like:

Index                location
1                 13/b srs mall, indirapuram,sann-444000
2                 NA
3                 12J 1st floor, jajan,totl-996633
4                 NA

Upvotes: 0

Views: 403

Answers (1)

cs95
cs95

Reputation: 402263

Use str.extract:

df['location'] = df.Text.str.extract('(?:address|contactus)(.*?\d{6})', expand=False)
df.drop('Text', 1)

   Index                                location
0      1  13/b srs mall, indirapuram,sann-444000
1      2                                     NaN
2      3        12J 1st floor, jajan,totl-996633

As a helpful aside, when you have multiple items to check for, put them in a list and join them with str.join:

terms = ['address', 'contactus', ...]

df['location'] = df.Text.str\
         .extract(r'(?:{})(.*?\d{6})'.format('|'.join(terms), expand=False)

Regex Details

(?:        # non-capturing group
address    # "address" 
|          # regex OR
contactus  # "contactus
)  
(.*?       # non-greedy match-all
\d{6}      # 6 digit zipcode
)

Upvotes: 1

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