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You have completed Introduction to NumPy!
You have completed Introduction to NumPy!
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Arrays can have multiple dimensions, let's see how to create and use them to our advantage.
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My Notes for Creating the Study Log
## About data types
* By choosing the proper [data type](https://docs.scipy.org/doc/numpy-1.14.0/user/basics.types.html) you can greatly reduce the size required to store objects
* Data types are maintained by wrapping values in a [scalar representation](https://docs.scipy.org/doc/numpy-1.14.0/reference/arrays.scalars.html)
* `np.zeros` is a handy way to create an empty array filled with zeros.
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especially in the context of an array?
0:00
Well, the answer is kind of boring
in comparison to how cool it sounds.
0:02
If you think about what we've been
doing so far with our arrays,
0:06
we've basically been building a container
where each slot represents something.
0:09
For instance,
in the grade point average example,
0:12
each element represented
a single year of school.
0:15
So we could say that this
is the year dimension.
0:18
Now let's imagine that we wanted to track
every student in my graduating class.
0:21
Now of course, we could add
a separate variable for each student.
0:25
But wouldn't it be nice to store
that all in the same variable.
0:29
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