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Vectorization and Broadcasting are what makes NumPy so fast. Pandas' data structures have similar super powers!

#### Example Code

##### Vectorization in NumPy

Arrays provide a **vectorized** method named add which removes the need for you to loop through each value to add things together.

```
np.array([1, 2, 3]) + np.array([4, 5, 6])
```

```
array([5, 7, 9])
```

##### Broadcasting in NumPy

Scalar values can be broadcasted to values, it's as if there was an equal sized array of all 1's.

```
conference_counts = np.array([4, 5, 10, 8, 15])
# Broadcast a scalar value
conference_counts + 1
```

```
array([ 5, 6, 11, 9, 16])
```

In the next step we'll see how to use vectorization and broadcasting in Pandas.

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