Calculate Percent Change Between Rows in Pandas Grouped by Another Column

I am somewhat new to Pandas and I have been stuck on a problem.

Assume I have the following dataframe (df1):

I would like to create another dataframe (df2) with each person's name and their percent improvement from Monday to Friday.

The result would be:

For example, Al improved by 17.33% between Monday and Friday (((88-75)/75) * 100)

Let us pivot to reshape then calculate pct change along column axis

s = df.pivot('Name', 'Day', 'Score')
s = s.pct_change(-1, axis=1)['Friday'].reset_index(name='Improvement')

Result

  Name  Improvement
0   Al     0.173333
1   Bo     0.111111
2   Cy     0.117647

If there is for each Name always ordered Monday and Friday like in sample data solution is GroupBy.pct_change:

df = (df[['Name']].join(df.groupby('Name')['Score'].pct_change().mul(100)
                          .rename('Improvement'))
                  .dropna())
print (df)
  Name  Improvement
1   Al    17.333333
3   Bo    11.111111
5   Cy    11.764706