Imports

Import matplotlib, the matplotlib.pylab and numpy, as they are needed in almost any case.

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

Simple plots

2D plots with X and Y axis data, no special formatting

plt.plot([1,2,6,4,7,9])
plt.ylabel('"random" numbers')
plt.xlabel('the X-axis is undefined and defaults to 0-5')
plt.show()

plt.plot([1,2,3,5], [1,4,9,16])
plt.ylabel('some numbers')
plt.xlabel('now the X-axis goes from 1 to 4')
plt.show()

Coloring the plots

The color formats are either RGB codes in the "#RRBBGG" or [RR, GG, BB] formats or one of the following basic built-in colors:

• b: blue
• g: green
• r: red
• c: cyan
• m: magenta
• y: yellow
• k: black
• w: white

plt.plot([1,2,3,4,5,6], [1,4,9,16, 20, 21], 'go')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.xlim(0,6*1.2)
plt.show()

Adding many data series to one plot with different colors

t = np.arange(0., 1., 0.04)
plt.plot(
    t, t, 'r--', 
    t, t**2, 'bs', 
    t, t**3, 'g^', 
    t, t**4, 'co'
)

plt.plot(t, t**3.5, 'k-')

plt.title(u'This plot also features many data series in one plot')
plt.xlabel('X')
plt.ylabel('different data series')
plt.show()

Defining colors using RGB codes

plt.plot([1,2,3,4,5,6], [1,4,9,16, 20, 21], linestyle='-', linewidth=2.0, color='#00aadd')
plt.plot([1,2,3,4,5,6], [2,5,10,17, 21, 22], linestyle='-', linewidth=2.0, color='#ff6700')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.title(u'Custom color using RGB code')
plt.xlim(0,7)
plt.show()

Axes

x=[1,2,3,4,5,6]
plt.plot(x, [1,4,9,16, 20.3, 21], 'go')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.axis([0, 8, 0, 33])
plt.grid(True)
plt.show()

x=[1,2,3,4,5,6]
labels=['First', 'Second', 'Third', 'Fourth', 'Fifth', 'Sixth']

plt.plot(x, [1,4,9,16, 20, 21], 'go')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.xticks(x, labels, rotation='vertical')
plt.axis([0, 7, 0, 33])
axes = plt.gca()
axes.xaxis.set_ticks_position('bottom')
axes.minorticks_on()
axes.yaxis.set_ticks_position('both')
plt.show()

Resizing a plot

x=[1,2,3,4,5,6]
plt.figure(figsize=(3,3))
plt.plot(x, [1,4,9,16, 20, 21], 'ko')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.axis([0, 8, 0, 33])
plt.show()

plt.figure(figsize=(5,2))
plt.plot(x, [1,4,9,16, 20, 21], 'ko')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.axis([0, 8, 0, 33])
plt.show()

Annotations

We can use LaTeX in the plots for any texts, eg. labels, annotations, etc.

plt.plot([1,2,3,3.1415,4,5,6], [1,4,9,3.1415**2.0,16, 20, 21], 'ro')
plt.ylabel('some numbers')
plt.xlabel('X')
plt.text(0.5, 25, r'This plot contains $\pi^2$ at $\pi$.', fontsize=20, color='#8900b6')
plt.annotate(r'This is $\pi^2$ at $\pi$!', xy=(3.1415+0.05, 3.1415**2.0-0.1), xytext=(3.5, 3),
            arrowprops=dict(facecolor='black', shrink=0.05), fontsize=20)
plt.axis([0, 8, 0, 33])
plt.grid(True)
plt.show()

Histrograms

mu, sigma = 100, 15
x = mu + sigma * np.random.randn(1000)

n, bins, patches = plt.hist(x, 20, facecolor='y', alpha=0.4)

plt.xlabel('X')
plt.ylabel('Number of data points in bins')
plt.title(r'Histogram example, $\mu=100,\ \sigma=15$')
plt.axis([40, 160, 0, 200])
plt.grid(True)
plt.show()

Subplots

x1 = np.linspace(0.0, 5.0)
x2 = np.linspace(0.0, 5.0)

y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

plt.figure(figsize=(6,6))

plt.subplot(2, 2, 1)
plt.title('A plot of 2 subplots')
plt.plot(x2, y2, 'g-')
plt.ylabel('Oscillation')

plt.subplot(2, 2, 2)
plt.plot(x1, y1, 'm--')
plt.ylabel('Damped oscillation')
plt.xlabel('time (s)')

plt.subplot(2, 2, 3)
plt.title('A plot of 2 subplots')
plt.plot(x2, y2, 'g-')
plt.ylabel('Oscillation')

plt.subplot(2, 2, 4)
plt.plot(x1, y1, 'm--')
plt.ylabel('Damped oscillation')
plt.xlabel('time (s)')

plt.tight_layout(pad=3.0)
plt.savefig("figure.pdf")
plt.savefig("figure.png")
plt.savefig("figure.svg")
plt.show()

Images

import matplotlib.image as mpimg
img=mpimg.imread('jupiter.jpg')
imgplot = plt.imshow(img)
plt.title('Jupiter')
plt.show()

import matplotlib.patches as patches
fig, ax = plt.subplots()
im = ax.imshow(img)
patch = patches.Circle((565, 545), radius=530, transform=ax.transData)
im.set_clip_path(patch)

plt.axis('off')
plt.title('Cropped Jupiter')
plt.show()

lum_img = img[:,:,0]
imgplot = plt.imshow(lum_img)
imgplot.set_cmap('winter') # or hot or winter or summer or etc.
plt.colorbar()
plt.title('False red channel color Jupiter')
plt.show()