Limpeza de dados em Python
Adel Nehme
VP of AI Curriculum, DataCamp
Todas as colunas têm os mesmos valores
| 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 |
A maioria das colunas tem os mesmos valores
| 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
# Pegar duplicatas em todas as colunas
duplicates = height_weight.duplicated()
print(duplicates)
1 False
... ....
22 True
23 False
... ...
# Obter linhas duplicadas
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
O método .duplicated()
subset: Lista de colunas para verificar duplicação.
keep: Manter a duplicata primeira ('first'), última ('last') ou todas (False).
# Colunas para checar duplicação
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
# Exibir valores duplicados
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
# Exibir valores duplicados
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
# Exibir valores duplicados
height_weight[duplicates].sort_values(by = 'first_name')

# Exibir valores duplicados
height_weight[duplicates].sort_values(by = 'first_name')

# Exibir valores duplicados
height_weight[duplicates].sort_values(by = 'first_name')

O método .drop_duplicates()
subset: Lista de colunas para verificar duplicação.
keep: Manter a duplicata primeira ('first'), última ('last') ou todas (False).
inplace: Remove as linhas duplicadas direto no DataFrame sem criar novo objeto (True).
# Remover duplicatas
height_weight.drop_duplicates(inplace = True)
# Exibir valores duplicados
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
# Exibir valores duplicados
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
height_weight[duplicates].sort_values(by = 'first_name')

Os métodos .groupby() e .agg()
# Agrupe pelas colunas e gere resumos estatísticos column_names = ['first_name','last_name','address'] summaries = {'height': 'max', 'weight': 'mean'} height_weight = height_weight.groupby(by = column_names).agg(summaries).reset_index()# Confira se a agregação foi feita duplicates = height_weight.duplicated(subset = column_names, keep = False) height_weight[duplicates].sort_values(by = 'first_name')
first_name last_name address height weight
Limpeza de dados em Python