11 Creating DataFrames in PySpark

Welcome to this Learning PySpark with Databricks YouTube series. This comprehensive series will get you from beginner to proficiency in PySpark. 🔗 Links & Resources Notebook GitHub Repository: https://github.com/pathfinder-analytics-uk/Learning-PySpark-with-Databricks Link to Notebook: https://github.com/pathfinder-analytics-uk/Learning-PySpark-with-Databricks/blob/main/11%20Creating%20DataFrames%20in%20PySpark.ipynb 🌐 Add me on LinkedIn: https://www.linkedin.com/in/malvik-vaghadia/ 💻Discount Codes To My Udemy Courses ✨Azure Databricks and Spark SQL: https://www.udemy.com/course/azure-databricks-and-spark-sql-python/?couponCode=YOUTUBE2025 ✨ Databricks SQL for Data Analysts: https://www.udemy.com/course/databricks-sql-for-data-analysts/?couponCode=YOUTUBE2025 ✨ dbt on Databricks: https://www.udemy.com/course/dbt-on-databricks/?couponCode=YOUTUBE2025 ✨ Python for Data Analysis: https://www.udemy.com/course/python-for-data-analysis-visualization/?couponCode=YOUTUBE2025 🕒 Timestamps 00:00 Introduction 00:26 Overview of createDataFrame method 02:35 createDataFrame demo 06:28 Defining the schema using column names 07:18 Specifying the schema using DDL (SQL syntax) 08:28 Overview of data types in Spark SQL 10:10 Explicit Schema Using StructType 14:10 Different Ways to Check Data Types in a DataFrame 15:20 createDataFrame demo with a list of dictionaries