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Scenario: Iceberg Lounge, Gotham’s most exclusive nightclub, serves as both a high-end establishment and a front for Penguin’s operations. As a contractor, you are consulting on various IT functions for the nightclub. Oswald Cobblepot, known as Penguin, has developed a solution using Microsoft Azure to support his business. Currently, the team is working with a Python DataFrame named salesData. To structure the data appropriately, the team must unpivot the DataFrame into a long-format dataset using pandas.melt(). The current project involves working with a Python dataframe named salesData . shop 2020 2021 0 ShopX 34 24 1 ShopY 65 76 2 ShopZ 48 55 The data frame must be unpivoted to a long data format as follows: shop year value 0 ShopX 2020 24 1 ShopY 2020 65 2 ShopZ 2020 48 3 ShopX 2020 25 4 ShopY 2021 76 5 ShopZ 2021 55 The Challenge: A developer has prepared the transformation code but is unsure which variable(s) should be passed into value_vars. They have left a placeholder ([?]) in the code: python import pandas as pd salesData = pd . melt ( salesData , id_vars =‘ shop ’, value_vars [?] The developer has asked for guidance on what should be used to complete the code segment. Question: Which of the following options should be advised for correctly specifying the value_vars argument in pandas?melt() function?