Creating a Pandas column based on values of another column using function

Question

I would like to identify doctors based on their title in a dataframe and create a new column to indicate if they are a doctor but I am struggling with my code.

doctorcriteria = ['Dr', 'dr']

def doctor(x):
  if doctorcriteria in x:
    return 'Doctor'
  else:
    return 'Not a doctor'

df['doctorcall'] = df.caller_name
df.doctorcall.fillna('Not a doctor', inplace=True)
df.doctorcall = df.doctorcall.apply(doctor)

kindly share a sample of your dataframe and ur expected output: stackoverflow.com/questions/20109391/… — sammywemmy
– sammywemmy, Commented Feb 13, 2020 at 9:27

Jamie · Accepted Answer · 2020-02-13 10:04:35Z

3

To create a new column with a function, you can use apply:

df = pd.DataFrame({'Title':['Dr', 'dr', 'Mr'],
               'Name':['John', 'Jim', 'Jason']})

doctorcriteria = ['Dr', 'dr']

def doctor(x):
    if x.Title in doctorcriteria:
        return 'Doctor'
    else: return 'Not a doctor'

df['IsDoctor'] = df.apply(doctor, axis=1)

But a more direct route to the answer would be to use map on the Title column.

doctor_titles = {'Dr', 'dr'}

df['IsDoctor'] = df['Title'].map(lambda title: title in doctor_titles)

edited Feb 13, 2020 at 10:04

answered Feb 13, 2020 at 9:21

Jamie

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1 Comment

Sanch Over a year ago

Thank you. How would I search in multiple columns for the same keywords?

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