pyspark.sql.DataFrame.drop

DataFrame.drop(*cols: ColumnOrName) → DataFrame

Returns a new DataFrame that drops the specified column. This is a no-op if schema doesn’t contain the given column name(s).

New in version 1.4.0.

Parameters

cols: str or :class:`Column`

a name of the column, or the Column to drop

Examples

>>> 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')]

pyspark.sql.DataFrame.distinct pyspark.sql.DataFrame.dropDuplicates