14. Databricks | Pyspark: Pivot & Unpivot

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[@ndbweurt34485]

highly underrated channel. no body has explained databricks so well.

[@rajasdataengineering7585]

Thank you

[@dhivyadouglas1681]

V true indeed

[@rajasdataengineering7585]

Thank you

[@gulsahtanay2341]

Thank you for your efforts to provide this content.

[@rajasdataengineering7585]

Glad you enjoy it!

[@avinash1722]

So well Articulated content.!!!

[@rajasdataengineering7585]

Thank you!

[@karthickraja1026]

Hi Raja, Thanks for this effort to make our self to boost pyspark knowledge. Can I know How to access all those code in the pyspark playlist?

[@Lord_JABA]

How to do the same unpivot but with multiple columns so for example if I have not only "company" but "company","category","randomCol" want them to be unchanged. so result is
columns :company, category, randomcol, quarter, revenue
same effect as DAX(powerbi): Table.Unpivot(#"step1", {"Q1","Q2"}, "Quarter", "Revenue")- which adds columns quarter and revenue leaving all the other columns present in the table multiplicated when needed

[@ranaumershamshad]

Videos are very informative, but the starting and ending music is so annoying.

[@rajasdataengineering7585]

Changed the starting music in later videos

[@purnimasharma9734]

Hi Raja, If you have more than 30 columns, is there a way to get the values dynamically (rather than typing each column's name and values) when you unpivot the data?

[@rajasdataengineering7585]

Hi Purnima, yes it is possible with python logic. Though I haven't done, it's certainly possible

[@sravanthireddy3849]

Hi Raja,
what about the interview do they ask syntax for functions ?? please reply

[@rajasdataengineering7585]

Hi Sravanthi, ideally interviewers are looking for the thought process of a candidate. So no exact syntax is expected

[@dunuker]

if i have multiple sum columns how should I perform

[@rock9278]

How to perform multiple Unpivot operations?

[@ashamaheshk7306]

How to perform unpivot in spark SQL?

[@rajasdataengineering7585]

select col1, stack(3, 'col2', col2, 'col3', col3, 'col4', col4) as (column,agg_value) from table