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
numpypackage asnp, so that you can refer tonumpywithnp. - Use
np.array()to create anumpyarray frombaseball. Name this arraynp_baseball. - Print out the type of
np_baseballto 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 dataWhat is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.