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Introduction to NumPy

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Boolean Array Indexing

12:51 with Craig Dennis

You can create an array of booleans and then use that to index into your array. Let's use this to filter our values.

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My Notes for Indexing 

## Creation 
* You can create a random but bound grouping of values using the `np.random` package.  
  * `RandomState` lets you seed your randomness in a way that is repeatable.
* You can append a row in a couple of ways
   * You can use the `np.append` method.  Make sure the new row is the same shape.
   * You can create/reassign a new array by including the existing array as part of the iterable in creation.


## Indexing
* You can use an indexing shortcut by separating dimensions with a comma.  
* You can index using a `list` or `np.array`.  Values will be pulled out at that specific index.  This is known as fancy indexing.
  * Resulting array shape matches the index array layout.  Be careful to distinguish between the tuple shortcut and fancy indexing.

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    We talked about creation and we saw a new way to build a random grouping of numbers. 0:00
    And we used RandomState to let us seed the randomness in a way that was repeatable. 0:01
    I have the same random values as you do. 0:05
    That is super handy. 0:07
    And we also learned that you can append a row in a couple of ways. 0:09
    There's even more that we haven't seen here. 0:12
    You can append, use the np.append method. 0:14
    You need to make sure that it's the same shape. 0:17
    Remember we did that little hack where we wrapped it in a list. 0:19
    And you can create and 0:22
    reassign a new array by including existing arrays as part of the iterable right? 0:24
    So you can throw the new array in there and 0:28

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