How I can get cartesian coordinate system in matplotlib?

Question

I am new to plotting with Python and can't really find an answer to the question: How can I get Cartesian coordinate plane in matplotlib? By this I mean perpendicular reference lines (coordinate axis) ended up with arrows, intersecting at the origin, (0,0), with the origin at the center of the plot.

Think about a a plane for doing high school geomtery, the following is a perfect example of what I need to achieve:

Answer 1

This is an old question, but I think with today's matplotlib versions, the keyword is spines. You would do:

ax = plt.gca() ax.spines['top'].set_color('none') ax.spines['bottom'].set_position('zero') ax.spines['left'].set_position('zero') ax.spines['right'].set_color('none') 

The link provides more examples.

Answer 2

Here is another way to draw a Cartesian coordinate system, built on the answers that have already been given.

import numpy as np                 # v 1.19.2 import matplotlib.pyplot as plt    # v 3.3.2  # Enter x and y coordinates of points and colors xs = [0, 2, -3, -1.5] ys = [0, 3, 1, -2.5] colors = ['m', 'g', 'r', 'b']  # Select length of axes and the space between tick labels xmin, xmax, ymin, ymax = -5, 5, -5, 5 ticks_frequency = 1  # Plot points fig, ax = plt.subplots(figsize=(10, 10)) ax.scatter(xs, ys, c=colors)  # Draw lines connecting points to axes for x, y, c in zip(xs, ys, colors):     ax.plot([x, x], [0, y], c=c, ls='--', lw=1.5, alpha=0.5)     ax.plot([0, x], [y, y], c=c, ls='--', lw=1.5, alpha=0.5)  # Set identical scales for both axes ax.set(xlim=(xmin-1, xmax+1), ylim=(ymin-1, ymax+1), aspect='equal')  # Set bottom and left spines as x and y axes of coordinate system ax.spines['bottom'].set_position('zero') ax.spines['left'].set_position('zero')  # Remove top and right spines ax.spines['top'].set_visible(False) ax.spines['right'].set_visible(False)  # Create 'x' and 'y' labels placed at the end of the axes ax.set_xlabel('x', size=14, labelpad=-24, x=1.03) ax.set_ylabel('y', size=14, labelpad=-21, y=1.02, rotation=0)  # Create custom major ticks to determine position of tick labels 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])  # Create minor ticks placed at each integer to enable drawing of minor grid # lines: note that this has no effect in this example with ticks_frequency=1 ax.set_xticks(np.arange(xmin, xmax+1), minor=True) ax.set_yticks(np.arange(ymin, ymax+1), minor=True)  # Draw major and minor grid lines ax.grid(which='both', color='grey', linewidth=1, linestyle='-', alpha=0.2)  # Draw arrows arrow_fmt = dict(markersize=4, color='black', clip_on=False) ax.plot((1), (0), marker='>', transform=ax.get_yaxis_transform(), **arrow_fmt) ax.plot((0), (1), marker='^', transform=ax.get_xaxis_transform(), **arrow_fmt)  plt.show() 

Notice that I have not added annotations displaying the coordinates of the points as in my experience, it requires a lot more code to position them nicely and have minimal overlapping. To get annotations, it is probably best to use the adjustText package or an interactive graphing library such as Plotly.