I have this dataframe:
Ubicacion lat lon
0 a 19.28034 -99.17121
1 b 19.28333 -99.17535
2 c 19.28028 -99.16887
3 a 19.28034 -99.17121
4 b 19.28333 -99.17535
5 c 19.28028 -99.16887
6 b 19.28333 -99.17535
7 d 19.29259 -99.17757
8 d 19.29259 -99.17757
9 d 19.29259 -99.17757
And I want to remove all duplicate rows, so I use:
ubicaciones_finales = ubicaciones_finales.drop_duplicates(keep="first")
And I get this:
Ubicacion lat lon
0 a 19.28034 -99.17121
1 b 19.28333 -99.17535
2 c 19.28028 -99.16887
7 d 19.29259 -99.17757
Everything seems fine except that rows go 0, 1, 2 and then 7. So when I run:
for k, row in ubicaciones_finales.iterrows():
print(k)
I get:
0
1
2
7
How do I solve this? btw, already check pandas documentation
df.drop_duplicates()
brand style rating
0 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0
And its the same, it goes from 0 to 2 witouth 1. Thank you for your time.
IIUC, go with reset_index
or simply pass ignore_index=True
:
df = df.drop_duplicates(keep='first').reset_index(drop=True)
# or
df = df.drop_duplicates(keep='first', ignore_index=True)
Output:
Ubicacion lat lon
0 a 19.28034 -99.17121
1 b 19.28333 -99.17535
2 c 19.28028 -99.16887
3 d 19.29259 -99.17757
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