Python으로 데이터 정제하기
Adel Nehme
VP of AI Curriculum, DataCamp
모든 열의 값이 동일함
| first_name | last_name | address | height | weight |
|---|---|---|---|---|
| Justin | Saddlemyer | Boulevard du Jardin Botanique 3, Bruxelles | 193 cm | 87 kg |
| Justin | Saddlemyer | Boulevard du Jardin Botanique 3, Bruxelles | 193 cm | 87 kg |
대부분의 열 값이 동일함
| first_name | last_name | address | height | weight |
|---|---|---|---|---|
| Justin | Saddlemyer | Boulevard du Jardin Botanique 3, Bruxelles | 193 cm | 87 kg |
| Justin | Saddlemyer | Boulevard du Jardin Botanique 3, Bruxelles | 194 cm | 87 kg |



# Print the header
height_weight.head()
first_name last_name address height weight
0 Lane Reese 534-1559 Nam St. 181 64
1 Ivor Pierce 102-3364 Non Road 168 66
2 Roary Gibson P.O. Box 344, 7785 Nisi Ave 191 99
3 Shannon Little 691-2550 Consectetuer Street 185 65
4 Abdul Fry 4565 Risus St. 169 65
# Get duplicates across all columns
duplicates = height_weight.duplicated()
print(duplicates)
1 False
... ....
22 True
23 False
... ...
# Get duplicate rows
duplicates = height_weight.duplicated()
height_weight[duplicates]
first_name last_name address height weight
100 Mary Colon 4674 Ut Rd. 179 75
101 Ivor Pierce 102-3364 Non Road 168 88
102 Cole Palmer 8366 At, Street 178 91
103 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 196 83
.duplicated() 메서드
subset: 중복을 확인할 열 이름 목록.
keep: 중복에서 어느 값을 유지할지 선택: 첫 번째('first'), 마지막('last'), 모두(False).
# 중복을 확인할 열 이름
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
# Output duplicate values
height_weight[duplicates]
first_name last_name address height weight
1 Ivor Pierce 102-3364 Non Road 168 66
22 Cole Palmer 8366 At, Street 178 91
28 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 195 83
37 Mary Colon 4674 Ut Rd. 179 75
100 Mary Colon 4674 Ut Rd. 179 75
101 Ivor Pierce 102-3364 Non Road 168 88
102 Cole Palmer 8366 At, Street 178 91
103 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 196 83
# Output duplicate values
height_weight[duplicates].sort_values(by = 'first_name')
first_name last_name address height weight
22 Cole Palmer 8366 At, Street 178 91
102 Cole Palmer 8366 At, Street 178 91
28 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 195 83
103 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 196 83
1 Ivor Pierce 102-3364 Non Road 168 66
101 Ivor Pierce 102-3364 Non Road 168 88
37 Mary Colon 4674 Ut Rd. 179 75
100 Mary Colon 4674 Ut Rd. 179 75
# Output duplicate values
height_weight[duplicates].sort_values(by = 'first_name')

# Output duplicate values
height_weight[duplicates].sort_values(by = 'first_name')

# Output duplicate values
height_weight[duplicates].sort_values(by = 'first_name')

.drop_duplicates() 메서드
subset: 중복을 확인할 열 이름 목록.
keep: 유지할 값 선택: 첫 번째('first'), 마지막('last'), 모두(False).
inplace: 새 객체 없이 DataFrame에서 직접 삭제 (True).
# 중복 제거
height_weight.drop_duplicates(inplace = True)
# Output duplicate values
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
height_weight[duplicates].sort_values(by = 'first_name')
first_name last_name address height weight
28 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 195 83
103 Desirae Shannon P.O. Box 643, 5251 Consectetuer, Rd. 196 83
1 Ivor Pierce 102-3364 Non Road 168 66
101 Ivor Pierce 102-3364 Non Road 168 88
# Output duplicate values
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
height_weight[duplicates].sort_values(by = 'first_name')

.groupby() 및 .agg() 메서드
# 열로 그룹화하고 통계 요약 생성 column_names = ['first_name','last_name','address'] summaries = {'height': 'max', 'weight': 'mean'} height_weight = height_weight.groupby(by = column_names).agg(summaries).reset_index()# 집계가 완료되었는지 확인 duplicates = height_weight.duplicated(subset = column_names, keep = False) height_weight[duplicates].sort_values(by = 'first_name')
first_name last_name address height weight
Python으로 데이터 정제하기