delete row from dataframe python
df.drop(df.index[-2])
df.drop(df.index[[3, 4]])
df.drop(['row_1', 'row_2'])
df.drop('column_1', axis=1)
df[df.name != 'cell']delete row from dataframe python
df.drop(df.index[-2])
df.drop(df.index[[3, 4]])
df.drop(['row_1', 'row_2'])
df.drop('column_1', axis=1)
df[df.name != 'cell']python pandas drop
df = pd.DataFrame(np.arange(12).reshape(3, 4),
... columns=['A', 'B', 'C', 'D'])
>>> df
A B C D
0 0 1 2 3
1 4 5 6 7
2 8 9 10 11
Drop columns
>>> df.drop(['B', 'C'], axis=1)
A D
0 0 3
1 4 7
2 8 11
>>> df.drop(columns=['B', 'C'])
A D
0 0 3
1 4 7
2 8 11Returns a new DataFrame that drops the specified column
# Returns a new DataFrame that drops the specified column
df.drop('age').collect()
# [Row(name='Alice'), Row(name='Bob')]
df.drop(df.age).collect()
# [Row(name='Alice'), Row(name='Bob')]
df.join(df2, df.name == df2.name, 'inner').drop(df.name).collect()
# [Row(age=5, height=85, name='Bob')]
df.join(df2, df.name == df2.name, 'inner').drop(df2.name).collect()
# [Row(age=5, name='Bob', height=85)]
df.join(df2, 'name', 'inner').drop('age', 'height').collect()
# [Row(name='Bob')]Copyright © 2021 Codeinu
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