How to delete columns in pyspark dataframe

953    Asked by ChrisDyer in Spark , Asked on Apr 19, 2021
>>> a
DataFrame[id: bigint, julian_date: string, user_id: bigint]
>>> b
DataFrame[id: bigint, quan_created_money: decimal(10,0), quan_created_cnt: bigint]
>>> a.join(b, a.id==b.id, 'outer')
DataFrame[id: bigint, julian_date: string, user_id: bigint, id: bigint, quan_created_money: decimal(10,0), quan_created_cnt: bigint]

 

There are two ids: bigint and I want to delete one. How can I do?

Answered by Chris Dyer

For Spark 1.4+ , Pyspark drop column function on a dataframe in order to remove a column.

You can use it in two ways:

df.drop('a_column').collect()
df.drop(df.a_column).collect()

Also, to drop multiple columns at a time you can use the following:

columns_to_drop = ['a column', 'b column']
df = df.drop(*columns_to_drop)

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