Subsetting 2D NumPy Arrays
If your 2D numpy array has a regular structure, i.e. each row and column has a fixed number of values, complicated ways of subsetting become very easy. Have a look at the code below where the elements "a" and "c" are extracted from a list of lists.
# numpy
import numpy as np
np_x = np.array(x)
np_x[:, 0]
The indexes before the comma refer to the rows, while those after the comma refer to the columns. The : is for slicing; in this example, it tells Python to include all rows.
This exercise is part of the course
Introduction to Python
Exercise instructions
- Print out the 50th row of
np_baseball. - Make a new variable,
np_weight_lb, containing the entire second column ofnp_baseball. - Select the height (first column) of the 124th baseball player in
np_baseballand print it out.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
import numpy as np
np_baseball = np.array(baseball)
# Print out the 50th row of np_baseball
# Select the entire second column of np_baseball: np_weight_lb
# Print out height of 124th player