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we will continue working with LaqnData.csv: a ) Run the following code, see its output, and then study the copde to answer what each line

we will continue working with LaqnData.csv:
a) Run the following code, see its output, and then study the copde to answer what each line of this code does:
air_df=pd.read_csv('LaqnData.csv')
air_df.drop(columns=["Site','Units','Provisional or Ratified'], inplace=True)
datetime_df=air_df.readingDatetime.str.split('',expand=True)
datetime_df.columns=['Date','Time]
date_df=datetime_df.Date.str.split('/',expand=True)
date_df.columns=['Day','Month','Year']
air_df=air_df.join(date_df.join(datetime_df.Time).drop(columns=['ReadingDateTime','Year'])
air_df
b) run the following code, see its output, and then study the code to answer what this line of code does:
air_df=air_df.set_index(['Month','Day','Time','Species'])
air_df
c) run the following code, see its output, and then study the code to answer what this line of code does:
air_df.unstack()
d) compare the output of the preceding code with pvt_df from Exercise 4. are they the same?
e)explain what the differences and similarities are between the pair .melt()/.pivot() and the pair .stack()/.unstack()?
f) if you were to choose one counterpartr for .melt() between .stack()/.unstack(), which one would you choose?

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