DataFrames and DatasetsHow do you create a DataFrame in PySpark?Explain the difference between a DataFrame and a Dataset in Spark.How can you perform joins in PySpark DataFrames? Give examples.What are some common DataFrame operations you use frequently?How do you handle missing data in a DataFra

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Creating and working with DataFrames in PySpark

To create a DataFrame in PySpark, you can use the createDataFrame() method from the SparkSession object.
DataFrames are structured and immutable collections of data, while Datasets are distributed collections of data with additional features like type-safety.
To perform joins in PySpark DataFrames, you can use the join() method with the appropriate join type (inner, outer, left, right).
Common DataFrame operations include filtering, grouping, aggregating, sorting, and selecting columns.
To handle missing data in a DataFrame, you can use the fillna() method to fill missing values with a specified default value.

DataFrames and DatasetsHow do you create a DataFrame in PySpark?Explain the difference between a DataFrame and a Dataset in Spark.How can you perform joins in PySpark DataFrames? Give examples.What are some common DataFrame operations you use frequently?How do you handle missing data in a DataFra

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