Cartesian coordinates with matplotlib

In this post we’ll create an orthonormal cartesian plane with x axis, y axis and origin, using matplotlib.

If you’re using jupyter first include this line to get inline charts:

%matplotlib inline

Add the required imports.

import numpy as np
import matplotlib.pyplot as plt

Define the x and y ranges, and the tick interval for both axes.

xmin, xmax, ymin, ymax = -5, 5, -5, 5
ticks_frequency = 1

Create a figure and an axes object. Also set the face color. This will cover transparent margins.

fig, ax = plt.subplots(figsize=(10, 10))

Apply the ranges to the axes.

ax.set(xlim=(xmin-1, xmax+1), ylim=(ymin-1, ymax+1), aspect='equal')

Set both axes to the zero position.


Hide the top and right spines.


Set the x and y labels, and add an origin label.

ax.set_xlabel('$x$', size=14, labelpad=-24, x=1.02)
ax.set_ylabel('$y$', size=14, labelpad=-21, y=1.02, rotation=0)
plt.text(0.49, 0.49, r"$O$", ha='right', va='top',
         horizontalalignment='center', fontsize=14)

Now create the x and the y ticks, and apply them to both axes.

x_ticks = np.arange(xmin, xmax+1, ticks_frequency)
y_ticks = np.arange(ymin, ymax+1, ticks_frequency)
ax.set_xticks(x_ticks[x_ticks != 0])
ax.set_yticks(y_ticks[y_ticks != 0])
ax.set_xticks(np.arange(xmin, xmax+1), minor=True)
ax.set_yticks(np.arange(ymin, ymax+1), minor=True)

Finally, add a grid.

ax.grid(which='both', color='grey', linewidth=1, linestyle='-', alpha=0.2)

Now our cartesian plane is ready and we can plot a function on it.

def func(x):
    return ((x - 1 ) ** 2) - 2
x = np.linspace(-5, 10, 100)
y = func(x)
plt.plot(x, y, 'b', linewidth=2)

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