PySpark: Select All Columns Except Specific Ones

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The easiest way to select all columns except specific ones in a PySpark DataFrame is by using the drop function.

Here are two common ways to do so:

Method 1: Select All Columns Except One

#select all columns except 'conference' column
df.drop('conference').show()

Method 2: Select All Columns Except Several Specific Ones

#select all columns except 'conference' and 'assists' columns
df.drop('conference', 'assists').show()

The following examples show how to use each method in practice with the following PySpark DataFrame:

from pyspark.sql import SparkSession
spark = SparkSession.builder.getOrCreate()

#define data
data = [['A', 'East', 11, 4], 
        ['A', 'East', 8, 9], 
        ['A', 'East', 10, 3], 
        ['B', 'West', 6, 12], 
        ['B', 'West', 6, 4], 
        ['C', 'East', 5, 2]] 
  
#define column names
columns = ['team', 'conference', 'points', 'assists'] 
  
#create dataframe using data and column names
df = spark.createDataFrame(data, columns) 
  
#view dataframe
df.show()

+----+----------+------+-------+
|team|conference|points|assists|
+----+----------+------+-------+
|   A|      East|    11|      4|
|   A|      East|     8|      9|
|   A|      East|    10|      3|
|   B|      West|     6|     12|
|   B|      West|     6|      4|
|   C|      East|     5|      2|
+----+----------+------+-------+

Example 1: Select All Columns Except One

We can use the following syntax to select all columns in the DataFrame except for the conference column:

#select all columns except 'conference' column
df.drop('conference').show()

+----+------+-------+
|team|points|assists|
+----+------+-------+
|   A|    11|      4|
|   A|     8|      9|
|   A|    10|      3|
|   B|     6|     12|
|   B|     6|      4|
|   C|     5|      2|
+----+------+-------+

Notice that the resulting DataFrame contains all columns from the original DataFrame except for the conference column.

Example 2: Select All Columns Except Several Specific Ones

We can use the following syntax to select all columns in the DataFrame except for the conference and assists columns:

#select all columns except 'conference' and 'assists' column
df.drop('conference', 'assists').show()

+----+------+
|team|points|
+----+------+
|   A|    11|
|   A|     8|
|   A|    10|
|   B|     6|
|   B|     6|
|   C|     5|
+----+------+

Notice that the resulting DataFrame contains all columns from the original DataFrame except for the conference and assists columns.