Dataframe splitting in Python-CodePudding

i Have a dataframe DF , and column name DETAILS, i want the value which are in double quotes (""), will make new column VALUE

DF=

      DETAILS                      
   Username as "JOHN"           
   verifying the name             
   click UserBox                  
   Password as "345678"          
   Click login                   
   click checkbox                 
   Phonenumber as "34512345"     
   Checking data

I want my data frame look like this

DF=

     DETAILS                      VALUE
   Username as "JOHN"           "JOHN"
   verifying the name             NA
   click UserBox                  NA
   Password as "345678"          "3345678"
   Click login                    NA
   click checkbox                 NA
   Phonenumber as "34512345"     "34512345"
   Checking data                 NA

CodePudding user response：

The str accessor has an extract method for that kind of use case:

DF['VALUE'] = DF['DETAILS'].str.extract('(".*?")')

With your data, it gives as expected:

                     DETAILS       VALUE
0         Username as "JOHN"      "JOHN"
1         verifying the name         NaN
2              click UserBox         NaN
3       Password as "345678"    "345678"
4                Click login         NaN
5             click checkbox         NaN
6  Phonenumber as "34512345"  "34512345"
7              Checking data         NaN

CodePudding user response：

Here you go:

df['VALUE'] = df.apply(
    lambda x: '"'   x['DETAILS'].split('"')[1]   '"' 
                if len(x['DETAILS'].split('"')) > 1 
                else 'NA',
    1)

This will output:

                     DETAILS       VALUE
0         Username as "JOHN"      "JOHN"
1         verifying the name          NA
2              click UserBox          NA
3       Password as "345678"    "345678"
4                Click login          NA
5             click checkbox          NA
6  Phonenumber as "34512345"  "34512345"
7              Checking data          NA

with the column VALUES containing your values where present, else NA.