Here is the article, https://medium.com/@tagnev.vengat/pyspark-transpose-rows-into-columns-cbaa55dcf754 Introduction: In data processing tasks, it’s often necessary to pivot data from a row-wise format to a column-wise format. This transformation, known as transposing rows into columns, is a common operation in data analysis and reporting tasks. PySpark, a powerful Python library for big data processing, offers multiple approaches to achieve this transformation. In this article, we’ll explore two different approaches and compare their effectiveness in handling missing values using the fillna method. If you found this video insightfut and wish to delve deeper into full-stack development or data engineering projects, I’d be thrilled to guide and collaborate further. Feel free to reach out through the mentioned channels below, and let’s make technology work for your unique needs. Contact Channels: LinkedIn Teckiy Twitter Substack Thank you for embarking on this journey with me through the realms of real-time data processing. Looking forward to our future collaborations. Snowflake Snowflake Connector Data Engineering