Table of Contents
There are two common ways to drop multiple columns in a PySpark DataFrame:
Method 1: Drop Multiple Columns by Name
#drop 'team' and 'points' columns df.drop('team', 'points').show()
Method 2: Drop Multiple Columns Based on List
#define list of columns to drop
drop_cols = ['team', 'points']
#drop all columns in list
df.select(*drop_cols).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: Drop Multiple Columns by Name
We can use the following syntax to drop the team and points columns from the DataFrame:
#drop 'team' and 'points' columns df.drop('team', 'points').show() +----------+-------+ |conference|assists| +----------+-------+ | East| 4| | East| 9| | East| 3| | West| 12| | West| 4| | East| 2| +----------+-------+
Notice that the team and points columns have both been dropped from the DataFrame, just as we specified.
Example 2: Drop Multiple Columns Based on List
We can use the following syntax to specify a list of column names and then drop all columns in the DataFrame that belong to the list:
#define list of columns to drop drop_cols = ['team', 'points'] #drop all columns in list df.drop(*drop_cols).show() +----------+-------+ |conference|assists| +----------+-------+ | East| 4| | East| 9| | East| 3| | West| 12| | West| 4| | East| 2| +----------+-------+
Notice that the resulting DataFrame drops each of the column names that we specified in the list.