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A global retail company sells products across multiple categories (e.

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A global retail company sells products across multiple categories (e.g.. Electronics, Clothing) and regions (e.g.. North. South, East. West). The sales team has provided the data engineer with a PySpark dataframe named sales_df as below and the team wants the data engineer to analyze the sales data to help them make strategic decisions.

A.

Category_sales = sales df.groupBy( " category " ).agg(sum( " sales amount " ) .alias ( " total sales amount " ))

B.

Category_sales = sales_df.sum( " 3ales_amount " ). g-1- upBy( " categcryn).alias( " toLal_sales_amount))

C.

Category_sale: .es df -agg (sum ( " sales amount " ) .-;r*i:rRy ( " category " ) .alias ( " total sa.en amount " ))

D.

Category_sales = sales_df.groupBy( " reqion " ). agq(sum( " sales_amountn).alias(ntotal_sales_amount ' ' ))

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