CODEWITHSUNDEEP
pythonpandasfunction
Demi
Demi

Reputation: 234

Error in function: get() can't be applied to a string (python)

let's suppose that my dataset looks like this:

ID School Name School Type Class size Specialization
0 New Jersey State School State School 7000 General
1 American International School Private International School 200 STEM
2 Boston Arts High School Private National School 500 Arts
3 New Hamptons Academy Private National School 300 Humanities
4 Colorado State School State School 10000 General
... ... ... ... ...

I have some key values being defined:

school_type_key={'State School':0, 'Private National School':1, 'Private International School':2}
specialization_key={'STEM':0,'Humanities':1,'Arts':2, 'Life Sciences':3, 'General':4, 'Other':5}

I need to write a function that:

  1. takes a column
  2. makes a list of unique value
  3. sorts this list based on defined keys
  4. returns a list

Here is what I tried:

def sort_by_keys(column):
    unique_values=df[column].unique()
    unique_values=list(unique_values)
    key=column.replace(' ','_').lower()+'_key'

    #I need key so that if i pass 'School Type' column, it is sorted by 'school_type_key'

    unique_values.sort(key=key.get, reverse=True)
    return unique_values

sort_by_keys('School Type')

However, it returns an error because key is a string and 'get' can't be applied towards a string. How can I solve this issue?

Expected output:

output=sort_by_keys('School Type')
print(output)
['State School', 'Private National School', 'Private International School']

output=sort_by_keys('Specialization')
print(output)
['STEM', 'Humanities','Arts','General']

Upvotes: 0

Views: 94

Answers (2)

René
René

Reputation: 4827

I don't understand exactly what you are trying to achieve. But based on your dictionary school_type_key, this could work for you.:

import pandas as pd
school_type_key={'State School':0, 'Private National School':1, 'Private International School':2}
df = pd.DataFrame({'School Type': school_type_key.keys()})
def sort_by_keys(column):
    return df[column].to_list()[::-1]
sort_by_keys('School Type')

Result:

['Private International School', 'Private National School', 'State School']

Upvotes: 1

Corralien
Corralien

Reputation: 120409

You can use:

MAPPING = {
    'School Type': school_type_key,
    'Specialization': specialization_key
}

def sort_by_keys(col):
    return (df[col].sort_values(key=lambda x: x.map(MAPPING[col]))
                   .unique().tolist())

Output:

>>> sort_by_keys('School Type')
['State School', 'Private National School', 'Private International School']

>>> sort_by_keys('Specialization')
['STEM', 'Humanities', 'Arts', 'General']

Upvotes: 2

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