How should you complete the code segment?

HOTSPOT

You have a Python data frame named salesData in the following format:

The data frame must be unpivoted to a long data format as follows:

You need to use the pandas.melt() function in Python to perform the transformation.

How should you complete the code segment? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

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Answer:

Explanation:

Box 1: dataFrame

Syntax: pandas.melt(frame, id_vars=None, value_vars=None, var_name=None, value_name=’value’, col_level=None)[source]

Where frame is a DataFrame

Box 2: shop

Paramter id_vars id_vars : tuple, list, or ndarray, optional

Column(s) to use as identifier variables.

Box 3: [‘2017′,’2018’]

value_vars : tuple, list, or ndarray, optional

Column(s) to unpivot. If not specified, uses all columns that are not set as id_vars.

Example:

df = pd.DataFrame({‘A’: {0: ‘a’, 1: ‘b’, 2: ‘c’},

…                    ‘B’: {0: 1, 1: 3, 2: 5},

…                    ‘C’: {0: 2, 1: 4, 2: 6}})

pd.melt(df, id_vars=[‘A’], value_vars=[‘B’, ‘C’])

A variable value

0  a     B      1

1  b     B      3

2  c     B      5

3  a     C      2

4  b     C      4

5  c     C      6

References: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.melt.html