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 6.2how to combine all columns into one column in r
unite(data, col, ..., sep = "_", remove = TRUE, na.rm = FALSE)after groupby how to add values in two rows to a list
In [1]: df = pd.DataFrame( {'a':['A','A','B','B','B','C'], 'b':[1,2,5,5,4,6]})
df
Out[1]:
a b
0 A 1
1 A 2
2 B 5
3 B 5
4 B 4
5 C 6
In [2]: df.groupby('a')['b'].apply(list)
Out[2]:
a
A [1, 2]
B [5, 5, 4]
C [6]
Name: b, dtype: object
In [3]: df1 = df.groupby('a')['b'].apply(list).reset_index(name='new')
df1
Out[3]:
a new
0 A [1, 2]
1 B [5, 5, 4]
2 C [6]Copyright © 2021 Codeinu
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