Columns
Get hands-on practice performing various operations on the columns of a DataFrame.
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Spark allows us to manipulate individual DataFrame columns using relational or computational expressions. Conceptually, columns represent a type of field and are similar to columns in pandas, R DataFrames, or relational tables. Columns are represented by the type Column in Spark’s supported languages. Let’s see some examples of working with columns next.
Listing all columns
We’ll assume we have already read the file BollywoodMovieDetail.csv in the DataFrame variable ...
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