matplotlib Part 2 – A Basic Matplotlib Example

# This magic command is only used in the IPython environment,
# so in the IPython console and in Jupyter Notebook. 
# It should be used only once per session, just like the imports 
# further down. If you use this command, all graphs will
# be embedded directly in the notebook rather than displayed
# in a separate window.
%matplotlib inline

# Here are the imports. Here you can also see the commonly
# used aliases for matplotlib and matplotlib.pyplot.
import matplotlib as mpl
import matplotlib.pyplot as plt

# We will also use numpy for this example.
import numpy as np

# And here's the example.
# First let's create an array of 100 evenly spaced numbers
# between -10 and 10. We can use the numpy linspace method
# to do that. These are going to be the X-coordinates.
# The method takes three parameters: the lower and upper
# range and the number of items.
x = np.linspace(-10, 10, 100)

# Now we're going to plot the following quadratic function:
# y = x ** 2 - 2 * x + 3, so we have:
y = x ** 2 - 2 * x + 3

# Now we have to generate the Figure instance and an Axes
# instance. The terms FIGURE and AXES are among the basic
# Matplotlib terms. A figure is the canvas area where one
# or more Axes instances can be added. An Axes instance is
# a region of the figure with its own individual coordinate
# system. There may be one area instance, like in the example
# below, but there may also be more.
# We can use the plt.subplots function to create a figure
# and an axis at the same time.
fig, ax = plt.subplots()

# And now let's finally plot the graph. Most functions we're 
# going to use are Axes methods.
ax.plot(x, y)

# Now hit Ctrl + Enter to execute the code.