find duplicated rows with respect to multiple columns pandas
df = df[df.duplicated(subset=['val1','val2'], keep=False)]
print (df)
id val1 val2
0 1 1.1 2.2
1 1 1.1 2.2
3 3 8.8 6.2
4 4 1.1 2.2
5 5 8.8 6.2find duplicated rows with respect to multiple columns pandas
df = df[df.duplicated(subset=['val1','val2'], keep=False)]
print (df)
id val1 val2
0 1 1.1 2.2
1 1 1.1 2.2
3 3 8.8 6.2
4 4 1.1 2.2
5 5 8.8 6.2python - show repeted values in a column
df = df[df.duplicated(subset=['val1','val2'], keep=False)]pandas.duplicated
>>> df.duplicated(subset=['brand'])
0 False
1 True
2 False
3 True
4 True
dtype: boolpandas.duplicated
>>> df.duplicated(keep='last')
0 True
1 False
2 False
3 False
4 False
dtype: boolcount duplicates in one column pandas
df.pivot_table(index=['DataFrame Column'], aggfunc='size')pandas.duplicated
>>> df = pd.DataFrame({
... 'brand': ['Yum Yum', 'Yum Yum', 'Indomie', 'Indomie', 'Indomie'],
... 'style': ['cup', 'cup', 'cup', 'pack', 'pack'],
... 'rating': [4, 4, 3.5, 15, 5]
... })
>>> df
brand style rating
0 Yum Yum cup 4.0
1 Yum Yum cup 4.0
2 Indomie cup 3.5
3 Indomie pack 15.0
4 Indomie pack 5.0Copyright © 2021 Codeinu
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