CODEWITHSUNDEEP
pythonpandasdataframedataset
Bestine Okinda
Bestine Okinda

Reputation: 31

Categorize age into another column age group

I have this dataset

age
24
32
29
23
23
31
25
26
34

I want to categorize using python and save the result to a new column "agegroup" such that age between; 23 to 26 to return 1 in the agegroup column, 27-30 to return value 2 in the agegroup column and 31-34 to return 3 in the agegroup column

Upvotes: 1

Views: 2208

Answers (2)

Abhishek
Abhishek

Reputation: 1

You can use dictionaries to do this as well. Key-value pairs. The keys would be the different age ranges and the value for a particular key would be the count for that particular age group.

groupDict={'23-26':0,'27-30':0,'31-34':0}

for i in ages:
 if i>=23 and i<=26:
   groupDict['23-26']+=1
 elif i>=27 and i<=30:
   groupDict['27-30']+=1
 elif i>=31 and i<=34:
   groupDict['27-30']+=1

Upvotes: 0

timgeb
timgeb

Reputation: 78690

You can use pandas.cut.

Given:

>>> df
   age
0   24
1   32
2   29
3   23
4   23
5   31
6   25
7   26
8   34

Solution:

>>> df.assign(agegroup=pd.cut(df['age'], bins=[23, 27, 31, 35], right=False, labels=[1, 2, 3]))
   age agegroup
0   24        1
1   32        3
2   29        2
3   23        1
4   23        1
5   31        3
6   25        1
7   26        1
8   34        3

Upvotes: 3

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