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Getting rows having nulls for a column
๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜ ๐Ÿ“˜๐Ÿ“˜๐Ÿ“˜๐Ÿ“˜๐Ÿ“˜๐Ÿ“˜๐Ÿ“˜
isNotNull() : True if the current expression is NOT null.
isNull() : True if the current expression is null.
With this you can get the total count of null or not null values in the column using PySpark
Read article : https://www.freshers.in/article/spark/pyspark-how-to-get-rows-having-nulls-for-a-column-or-columns-without-nulls-or-count-of-non-null/
Get complete source code in the above article
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PySpark how to get rows having nulls for a column or columns without nulls or count of Non null - Freshers.in

pyspark.sql.Column.isNotNull isNotNull() : True if the current expression is NOT null. isNull() : True if the current expression is null. With this you can get the total count of null or not null values in the column using PySpark from pyspark.sql import SparkSession spark = SparkSession.builder.appName("isNotNull @ Freshers.in ").getOrCreate() emp_schema= ["name","id","age","gender","dept","state","salary","increment"] emp_data = [ ("Sam",1010,30,"Male","IT",None,125000,8.1), ("Peter",1020,32,"Male","HR","NY",90000,7.0),

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Efficiently Processing Large Text Files in Python
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Processing large text files efficiently is a common challenge faced by programmers dealing with vast amounts of data. In this guide, weโ€™ll explore various techniques to enhance the performance of your Python scripts when handling massive text files.

Sample code with Data in the link

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https://www.freshers.in/article/python/efficiently-processing-large-text-files-in-python/

Efficiently Processing Large Text Files in Python - Freshers.in

Learn how to supercharge your text file processing in Python! Dive into efficient techniques, optimizations, and a real-world example to boost performance. Master large-scale data handling effortlessly.

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Verbal and Reasoning - Freshers.in

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