Data opschonen in Python
Adel Nehme
VP of AI Curriculum, DataCamp
Alle kolommen hebben dezelfde waarden
| 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 |
De meeste kolommen hebben dezelfde waarden
| 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 de kop
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
# Duplicaten over alle kolommen
duplicates = height_weight.duplicated()
print(duplicates)
1 False
... ....
22 True
23 False
... ...
# Dubbele rijen ophalen
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
De methode .duplicated()
subset: Lijst met kolomnamen om op duplicaten te checken.
keep: Bewaar de eerste ('first'), laatste ('last') of alle (False) duplicaten.
# Kolomnamen om op duplicatie te checken
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
# Dubbele waarden weergeven
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
# Dubbele waarden weergeven
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
# Dubbele waarden weergeven
height_weight[duplicates].sort_values(by = 'first_name')

# Dubbele waarden weergeven
height_weight[duplicates].sort_values(by = 'first_name')

# Dubbele waarden weergeven
height_weight[duplicates].sort_values(by = 'first_name')

De methode .drop_duplicates()
subset: Lijst met kolomnamen om op duplicaten te checken.
keep: Bewaar de eerste ('first'), laatste ('last') of alle (False) duplicaten.
inplace: Verwijder dubbele rijen direct in de DataFrame zonder nieuw object te maken (True).
# Duplicaten verwijderen
height_weight.drop_duplicates(inplace = True)
# Dubbele waarden weergeven
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
# Dubbele waarden weergeven
column_names = ['first_name','last_name','address']
duplicates = height_weight.duplicated(subset = column_names, keep = False)
height_weight[duplicates].sort_values(by = 'first_name')

De methoden .groupby() en .agg()
# Groepeer op kolomnamen en maak statistische samenvattingen column_names = ['first_name','last_name','address'] summaries = {'height': 'max', 'weight': 'mean'} height_weight = height_weight.groupby(by = column_names).agg(summaries).reset_index()# Controleren of de aggregatie is gedaan duplicates = height_weight.duplicated(subset = column_names, keep = False) height_weight[duplicates].sort_values(by = 'first_name')
first_name last_name address height weight
Data opschonen in Python