Converting categorical variables to numbers based on frequency in a single line

Question

This is similar to LabelEncoder from scikit-learn, but with the requirement that the number value assignments occur in order of frequency of the category, i.e., the higher occurring category being assigned the highest/lowest (depending on use-case) number.

E.g. If the variable can take values [a, b, c] with frequencies such as

  Category 
0        a 
0        a 
0        a 
0        a 
0        a 
1        b 
1        b 
1        b 
1        b 
1        b 
1        b 
1        b 
1        b 
1        b 
1        b 
2        c 
2        c 

a occurs 5 times, b occurs 10 times and c occurs 2 times. Then I want the replacements be done as b=1, a=2 and c=3.

Answer 1

See argsort:

df['Order'] = df['Frequency'].argsort() + 1
df

returns

  Category  Frequency  Order
0        a          5      3
1        b         10      1
2        c          2      2

Answer 2

If you are using pandas, you can use its map() method:

import pandas as pd
data = pd.DataFrame([['a'], ['b'], ['c']], columns=['category'])

print(data)

  category
0        a
1        b
2        c

mapping_dict = {'b':1, 'a':2, 'c':3}

print(data['category'].map(mapping_dict))

0    2
1    1
2    3

LabelEncoder uses np.unique to find the unique values present in a column which returns values in alphabetically sorted order, so you cannot use the custom ordering in it.