Update 01-numpy.md

Removed 4 exercises that were duplicates from higher up in the page.

Author: mboisson

01-numpy.md

@@ -658,59 +658,6 @@ the graphs will actually be squeezed together more closely.)
 > If you ever see Python code online using a NumPy function with `np`
 > (for example, `np.loadtxt(...)`), it's because they've used this shortcut.
 
-> ## Check your understanding {.challenge}
->
-> Draw diagrams showing what variables refer to what values after each statement in the following program:
->
-> ~~~ {.python}
-> mass = 47.5
-> age = 122
-> mass = mass * 2.0
-> age = age - 20
-> ~~~
-
-> ## Sorting out references {.challenge}
->
-> What does the following program print out?
->
-> ~~~ {.python}
-> first, second = 'Grace', 'Hopper'
-> third, fourth = second, first
-> print third, fourth
-> ~~~
-
-> ## Slicing strings {.challenge}
->
-> A section of an array is called a [slice](reference.html#slice).
-> We can take slices of character strings as well:
->
-> ~~~ {.python}
-> element = 'oxygen'
-> print 'first three characters:', element[0:3]
-> print 'last three characters:', element[3:6]
-> ~~~
->
-> ~~~ {.output}
-> first three characters: oxy
-> last three characters: gen
-> ~~~
->
-> What is the value of `element[:4]`?
-> What about `element[4:]`?
-> Or `element[:]`?
->
-> What is `element[-1]`?
-> What is `element[-2]`?
-> Given those answers,
-> explain what `element[1:-1]` does.
-
-> ## Thin slices {.challenge}
->
-> The expression `element[3:3]` produces an [empty string](reference.html#empty-string),
-> i.e., a string that contains no characters.
-> If `data` holds our array of patient data,
-> what does `data[3:3, 4:4]` produce?
-> What about `data[3:3, :]`?
 
 > ## Check your understanding: plot scaling {.challenge}
 >