Ndarray Indexing

## Description

ndarray objects use a similar indexing system to iterable Python data types. To access an element of a multidimensional array, we use an "outside-in" approach. For instance, to access the location of the number 7 in the following 3 dimensional array a:

``````[[[1 2]
[3 4]]

[[5 6]
[7 8]]]```
```

we would call the index of the 2-dimensional array containing [5 6] and [7 8], then the index of 7 in the 1-dimensional array containing 7 like so: a[1, 1, 0]

## Sage Cell

#### Code

``````a = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
print(a[1, 1, 0])```
```

## Options

#### Slicing Arrays

We can take multiple items at once by passing a range of indices instead of only one using :. For instance, if we wanted all items in an array b from index 0 to index 5, we would use 0:6. We can also tell the program to simply get everything to the end of the array by leaving the range unbounded, like so: 0:. Note the last number in the given range is excluded. As an example, the following cell shows how to get the first item in every 1 -dimensional array stored in 3 dimensional array a.

#### Code

``````a = np.array([[[1, 2], [3, 4]], [[5, 6], [7, 8]]])
print(a[0:, 0:, 0])```
```

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