In [73]:
%matplotlib inline
In [74]:
from pylab import *
import matplotlib
import matplotlib.pyplot as plt
import numpy as np

In addition to the regular plot method, there are a number of other functions for generating different kind of plots. See the matplotlib plot gallery for a complete list of available plot types: Some of the more useful ones are show below:

In [75]:
n = np.array([0,1,2,3,4,5])
In [76]:
fig, axes = plt.subplots(1, 4, figsize=(12,3))

axes[0].scatter(xx, xx + 0.25*np.random.randn(len(xx)))

axes[1].step(n, n**2, lw=2)

axes[2].bar(n, n**2, align="center", width=0.5, alpha=0.5)

axes[3].fill_between(x, x**2, x**3, color="green", alpha=0.5);
In [77]:
from mpl_toolkits.mplot3d.axes3d import Axes3D
In [78]:
fig = plt.figure(figsize=(14,6))

# `ax` is a 3D-aware axis instance because of the projection='3d' keyword argument to add_subplot
ax = fig.add_subplot(1, 2, 1, projection='3d')

p = ax.plot_surface(X, Y, Z, rstride=4, cstride=4, linewidth=0)

# surface_plot with color grading and color bar
ax = fig.add_subplot(1, 2, 2, projection='3d')
p = ax.plot_surface(X, Y, Z, rstride=1, cstride=1,, linewidth=0, antialiased=False)
cb = fig.colorbar(p, shrink=0.5)