close

How to filter a Spark dataframe by a boolean column?

Hello Guys, How are you all? Hope You all Are Fine. Today We Are Going To learn about How to filter a Spark dataframe by a boolean column in Python. So Here I am Explain to you all the possible Methods here.

Without wasting your time, Let’s start This Article.

Table of Contents

How to filter a Spark dataframe by a boolean column?

  1. How to filter a Spark dataframe by a boolean column?

    You're comparing data types incorrectly. open is listed as a Boolean value, not a string, so doing yelp_df["open"] == "true" is incorrect – "true" is a string.

  2. filter a Spark dataframe by a boolean column

    You're comparing data types incorrectly. open is listed as a Boolean value, not a string, so doing yelp_df["open"] == "true" is incorrect – "true" is a string.

Method 1

You’re comparing data types incorrectly. open is listed as a Boolean value, not a string, so doing yelp_df["open"] == "true" is incorrect – "true" is a string.

Instead you want to do

yelp_df.filter(yelp_df["open"] == True).collect()

This correctly compares the values of open against the Boolean primitive True, rather than the non-Boolean string "true".

Method 2

from pyspark.sql import functions as F

filtered_df = df.filter(F.col('my_bool_col'))

Summery

It’s all About this issue. Hope all Methods helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which Method worked for you? Thank You.

Also, Read