DataFrame 원하는 조건에 값 넣기

import pandas as pd
from sklearn.datasets import load_iris

iris = load_iris()
iris = pd.DataFrame(iris.data, columns=iris.feature_names)
iris["Class"]=load_iris().target

iris

	sepal length (cm)	sepal width (cm)	petal length (cm)	petal width (cm)	Class
0	5.1	3.5	1.4	0.2	0
1	4.9	3.0	1.4	0.2	0
2	4.7	3.2	1.3	0.2	0
3	4.6	3.1	1.5	0.2	0
4	5.0	3.6	1.4	0.2	0
...	...	...	...	...	...
145	6.7	3.0	5.2	2.3	2
146	6.3	2.5	5.0	1.9	2
147	6.5	3.0	5.2	2.0	2
148	6.2	3.4	5.4	2.3	2
149	5.9	3.0	5.1	1.8	2

150 rows × 5 columns

Class 단위로 카운트값을 새로운 컬럼에 추가하기¶

Class에 조건을 건다 -> 새로운컬럼에 값을 넣는다 ??¶

iris[iris['Class']==0] # Class가 0인 값들

	sepal length (cm)	sepal width (cm)	petal length (cm)	petal width (cm)	Class
0	5.1	3.5	1.4	0.2	0
1	4.9	3.0	1.4	0.2	0
2	4.7	3.2	1.3	0.2	0
3	4.6	3.1	1.5	0.2	0
4	5.0	3.6	1.4	0.2	0
5	5.4	3.9	1.7	0.4	0
6	4.6	3.4	1.4	0.3	0
7	5.0	3.4	1.5	0.2	0
8	4.4	2.9	1.4	0.2	0
9	4.9	3.1	1.5	0.1	0
10	5.4	3.7	1.5	0.2	0
11	4.8	3.4	1.6	0.2	0
12	4.8	3.0	1.4	0.1	0
13	4.3	3.0	1.1	0.1	0
14	5.8	4.0	1.2	0.2	0
15	5.7	4.4	1.5	0.4	0
16	5.4	3.9	1.3	0.4	0
17	5.1	3.5	1.4	0.3	0
18	5.7	3.8	1.7	0.3	0
19	5.1	3.8	1.5	0.3	0
20	5.4	3.4	1.7	0.2	0
21	5.1	3.7	1.5	0.4	0
22	4.6	3.6	1.0	0.2	0
23	5.1	3.3	1.7	0.5	0
24	4.8	3.4	1.9	0.2	0
25	5.0	3.0	1.6	0.2	0
26	5.0	3.4	1.6	0.4	0
27	5.2	3.5	1.5	0.2	0
28	5.2	3.4	1.4	0.2	0
29	4.7	3.2	1.6	0.2	0
30	4.8	3.1	1.6	0.2	0
31	5.4	3.4	1.5	0.4	0
32	5.2	4.1	1.5	0.1	0
33	5.5	4.2	1.4	0.2	0
34	4.9	3.1	1.5	0.2	0
35	5.0	3.2	1.2	0.2	0
36	5.5	3.5	1.3	0.2	0
37	4.9	3.6	1.4	0.1	0
38	4.4	3.0	1.3	0.2	0
39	5.1	3.4	1.5	0.2	0
40	5.0	3.5	1.3	0.3	0
41	4.5	2.3	1.3	0.3	0
42	4.4	3.2	1.3	0.2	0
43	5.0	3.5	1.6	0.6	0
44	5.1	3.8	1.9	0.4	0
45	4.8	3.0	1.4	0.3	0
46	5.1	3.8	1.6	0.2	0
47	4.6	3.2	1.4	0.2	0
48	5.3	3.7	1.5	0.2	0
49	5.0	3.3	1.4	0.2	0

새로운 컬럼에 숫자값을 넣어보자¶

iris["idx"]=0

iris.head()

	sepal length (cm)	sepal width (cm)	petal length (cm)	petal width (cm)	Class	idx
0	5.1	3.5	1.4	0.2	0	0
1	4.9	3.0	1.4	0.2	0	0
2	4.7	3.2	1.3	0.2	0	0
3	4.6	3.1	1.5	0.2	0	0
4	5.0	3.6	1.4	0.2	0	0

iris[iris['Class']==0]["idx"]=1

C:\Users\jun\AppData\Local\Temp\ipykernel_12876\2747504533.py:1: SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  iris[iris['Class']==0]["idx"]=1

경고가 뜨면서 값 이 추가되지 않습니다.¶

이문제를 해결 하는 방법입니다.¶

경고 문구에 있는 .loc[] 를 이용하는 방법이 있겠지만¶

여기에서는 복사한뒤 넣는 방법을 사용합니다.¶

방법은 아래와 같습니다.¶

iris_cpy=iris[iris['Class']==0].copy()

iris_cpy.head()

	sepal length (cm)	sepal width (cm)	petal length (cm)	petal width (cm)	Class	idx
0	5.1	3.5	1.4	0.2	0	0
1	4.9	3.0	1.4	0.2	0	0
2	4.7	3.2	1.3	0.2	0	0
3	4.6	3.1	1.5	0.2	0	0
4	5.0	3.6	1.4	0.2	0	0

iris_cpy["idx"]=1

iris[iris['Class']==0]=iris_cpy

iris.head()

	sepal length (cm)	sepal width (cm)	petal length (cm)	petal width (cm)	Class	idx
0	5.1	3.5	1.4	0.2	0	1
1	4.9	3.0	1.4	0.2	0	1
2	4.7	3.2	1.3	0.2	0	1
3	4.6	3.1	1.5	0.2	0	1
4	5.0	3.6	1.4	0.2	0	1

idx 에 1이라는 값을 넣었습니다.¶

이번에는 정해진 상수가 아니라 index를 넣어보겠습니다.¶

iris_uni=iris["Class"].unique()
iris_uni

array([0, 1, 2])

df = iris.copy()

x = 0
def fun_idx(a):
    global x
    x = x + 1
    return x

for uni in iris_uni:
    iris_cpy=df[df['Class']==uni].copy()
    x = 0
    iris_cpy["idx"]=iris_cpy["idx"].apply(fun_idx)
    df[df['Class']==uni]=iris_cpy

df

	sepal length (cm)	sepal width (cm)	petal length (cm)	petal width (cm)	Class	idx
0	5.1	3.5	1.4	0.2	0	1
1	4.9	3.0	1.4	0.2	0	2
2	4.7	3.2	1.3	0.2	0	3
3	4.6	3.1	1.5	0.2	0	4
4	5.0	3.6	1.4	0.2	0	5
...	...	...	...	...	...	...
145	6.7	3.0	5.2	2.3	2	46
146	6.3	2.5	5.0	1.9	2	47
147	6.5	3.0	5.2	2.0	2	48
148	6.2	3.4	5.4	2.3	2	49
149	5.9	3.0	5.1	1.8	2	50

150 rows × 6 columns

idx 에 원하는 값들이 표기가 되었습니다.¶