'''
Pivot data

Pivoting data is the opposite of melting it. Remember the tidy form that the 
airquality DataFrame was in before you melted it? You'll now begin pivoting it back 
into that form using the .pivot_table() method!

While melting takes a set of columns and turns it into a single column, pivoting 
will create a new column for each unique value in a specified column.

.pivot_table() has an index parameter which you can use to specify the columns that 
you don't want pivoted: It is similar to the id_vars parameter of pd.melt(). 
Two other parameters that you have to specify are columns (the name of the column 
you want to pivot), and values (the values to be used when the column is pivoted). 
The melted DataFrame airquality_melt has been pre-loaded for you.

INSTRUCTIONS
100 XP
Print the head of airquality_melt.
Pivot airquality_melt by using .pivot_table() with the rows indexed by 
'Month' and 'Day', the columns indexed by 'measurement', and the values 
populated with 'reading'.
Print the head of airquality_pivot.
'''
