[Python] How to map numeric data into categories / bins in Pandas dataframe

I have a pandas dataframe:



It has around 3m rows. There are 3 kinds of age_units: Y, D, W for years, Days & Weeks. Any individual over 1 year old has an age unit of Y and my first grouping I want is <2y old so all I have to test for in Age Units is Y...

I want to create a new column AgeRange and populate with the following ranges:

• <2
• 2 - 18
• 18 - 35
• 35 - 65
• 65+

so I wrote a function

def agerange(values):
for i in values:
if complete.Age_units == 'Y':
if complete.Age > 1 AND < 18 return '2-18'
elif complete.Age > 17 AND < 35 return '18-35'
elif complete.Age > 34 AND < 65 return '35-65'
elif complete.Age > 64 return '65+'
else return '< 2'


I thought if I passed in the dataframe as a whole, I would get back what I needed and then could create the column I wanted something like this:

agedetails['age_range'] = ageRange(agedetails)


BUT when I try to run the first code to create the function I get:

File "<ipython-input-124-cf39c7ce66d9>", line 4
if complete.Age > 1 AND complete.Age < 18 return '2-18'
^
SyntaxError: invalid syntax


Clearly it is not accepting the AND - but I thought I heard in class I could use AND like this? I must be mistaken but then what would be the right way to do this?

So after getting that error, I'm not even sure the method of passing in a dataframe will throw an error either. I am guessing probably yes. In which case - how would I make that work as well?

I am looking to learn the best method, but part of the best method for me is keeping it simple even if that means doing things in a couple of steps...

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