# Your First NumPy Array

You're now going to dive into the world of baseball. Along the way, you'll get comfortable with the basics of `numpy`

, a powerful package to do data science.

A list `baseball`

has already been defined in the Python script, representing the height of some baseball players in centimeters. Can you add some code to create a `numpy`

array from it?

This is a part of the course

## “Introduction to Python”

### Exercise instructions

- Import the
`numpy`

package as`np`

, so that you can refer to`numpy`

with`np`

. - Use
`np.array()`

to create a`numpy`

array from`baseball`

. Name this array`np_baseball`

. - Print out the type of
`np_baseball`

to check that you got it right.

### Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

```
# Import the numpy package as np
baseball = [180, 215, 210, 210, 188, 176, 209, 200]
# Create a numpy array from baseball: np_baseball
# Print out type of np_baseball
```

This exercise is part of the course

## Introduction to Python

Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.

NumPy is a fundamental Python package to efficiently practice data science. Learn to work with powerful tools in the NumPy array, and get started with data exploration.

Exercise 1: NumPyExercise 2: Your First NumPy ArrayExercise 3: Baseball players' heightExercise 4: NumPy Side EffectsExercise 5: Subsetting NumPy ArraysExercise 6: 2D NumPy ArraysExercise 7: Your First 2D NumPy ArrayExercise 8: Baseball data in 2D formExercise 9: Subsetting 2D NumPy ArraysExercise 10: 2D ArithmeticExercise 11: NumPy: Basic StatisticsExercise 12: Average versus medianExercise 13: Explore the baseball data### What is DataCamp?

Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.