Matplotlib Pyplot Cheat Sheet 2023

Matplotlib Pyplot Cheat Sheet 2023
- Functional API
  - Generate Data
  - Line Plot
- Figure Object API

Functional API

import matplotlib.pyplot as plt
import numpy as np
from numpy.random import randint

Generate Data

x = np.arange(-10,10)
y = x**2

a = np.linspace(0,10,20)
b = a**5+a**2

np.random.seed(42)
xz = 4 + np.random.normal(0, 2, 24)
yz = 4 + np.random.normal(0, 2, len(xz))

rand = randint(1,50,20)

name_array = ['First Dataset', 'Second Dataset', 'Third Dataset']
x_array = [rand, rand-15, rand**(1/2)]
y_array = [rand**(3/4), rand**2, rand**(2/3)]

Line Plot

plt.plot(x, y)
plt.xlabel('X Axis')
plt.ylabel('Y Axis')
plt.xlim(-9, 9)
plt.ylim(0, 80)
plt.title('Smile!')
plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_01.webp')

Figure Object API

Line Plot

figure = plt.figure(figsize=(10,10))
# add_axes[(lower left corner x,y), width&height of plot inside figure [0-1]]
axes = figure.add_axes([0,0,1,0.2])
# start plot at 0,0 and use 100% width but only 20% height
axes.plot(x, y)

fig = plt.figure(figsize=(10,5))

ax_xy = fig.add_axes([0.1,0.1,0.5,0.8])
ax_xy.plot(x, y)
ax_xy.set_xlim(-10, 10)
ax_xy.set_ylim(0, 100)
ax_xy.set_xlabel('X Axis')
ax_xy.set_ylabel('Y Axis')
ax_xy.set_title('A/B Plot Title')

ax_ab_sub1 = fig.add_axes([0.68,0.6,0.3,0.3])
ax_ab_sub1.plot(a, b)
ax_ab_sub1.set_xlim(3,6)
ax_ab_sub1.set_ylim(0, 5000)
ax_ab_sub1.set_xlabel('A Axis')
ax_ab_sub1.set_ylabel('B Axis')
ax_ab_sub1.set_title('X/Y Plot Title')

ax_ab_sub2 = fig.add_axes([0.68,0.1,0.3,0.3])
ax_ab_sub2.plot(a, b)
ax_ab_sub2.set_xlim(7,10)
ax_ab_sub2.set_ylim(25000, 75000)
ax_ab_sub2.set_xlabel('A Axis')
ax_ab_sub2.set_ylabel('B Axis')
ax_ab_sub2.set_title('X/Y Plot Title')

fig.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_03.webp', bbox_inches='tight')

Subplots

fig, axes = plt.subplots(figsize=(10,5), nrows=1, ncols=2)

axes[0].plot(x, y)
axes[1].plot(a, b)

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_04.webp')

fig, axes = plt.subplots(figsize=(10, 5), nrows=2, ncols=2)

fig.suptitle('Plot Title')

axes[0][0].plot(x, y)
axes[0][0].set_xlabel('X Axis')
axes[0][0].set_ylabel('Y Axis')
axes[0][0].set_title('X/Y Title')

axes[0][1].plot(a, b)
axes[0][1].set_xlabel('A Axis')
axes[0][1].set_ylabel('B Axis')
axes[0][1].set_title('A/B Title')

axes[1][0].plot(a, b)
axes[1][0].set_xlabel('A Axis')
axes[1][0].set_ylabel('B Axis')
axes[1][0].set_title('A/B Title')

axes[1][1].plot(x, y)
axes[1][1].set_xlabel('X Axis')
axes[1][1].set_ylabel('Y Axis')
axes[1][1].set_title('X/Y Title')

fig.subplots_adjust(
    left=None,
    bottom=None,
    right=None,
    top=None,
    wspace=0.5,
    hspace=1
)

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_05.webp')

fig, axes = plt.subplots(figsize=(10,5), nrows=3, ncols=1)

fig.suptitle('I am Scattered')

counter = 0

for ax in axes:
    ax.plot(
        x_array[counter],
        y_array[counter],
        color='g',
        marker='P',
        linestyle='None'
    )
    ax.set_title(name_array[counter])
    counter += 1
    
plt.tight_layout()

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_06.webp')

Legend

fig = plt.figure(figsize=(12,8))

ax = fig.add_axes([0,0,1,1])

ax.plot(a, a**(4/3), label="x, x**4/3")
ax.plot(a, a, label="x, x")
ax.plot(a, a**(2/3), label="x, x**2/3")
ax.plot(a, a**(1/2), label="x, x**1/2")

ax.legend(loc='upper left')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_07.webp', bbox_inches='tight')

fig = plt.figure(figsize=(12,8))

ax = fig.add_axes([0,0,1,1])

ax.plot(a, a**(4/3), label="x, x**4/3")
ax.plot(a, a, label="x, x")
ax.plot(a, a**(2/3), label="x, x**2/3")
ax.plot(a, a**(1/2), label="x, x**1/2")

ax.legend(loc=(1.1, 0.9))
plt.tight_layout()

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_08.webp', bbox_inches='tight')

Styling

fig = plt.figure(figsize=(12,8))

ax = fig.add_axes([0,0,1,1])

ax.plot(
    a,a,
    color='dodgerblue',
    linewidth='5',
    label="a, a"
)
ax.plot(
    a,(a**(3/2)+b**(1/2)),
    color='#fd18d9',
    linestyle='dashed',
    marker='h',
    markersize=16,
    markerfacecolor='lightseagreen',
    markeredgewidth=3,
    markeredgecolor='fuchsia',
    label="a,(a**(3/2)+b**(1/2)"
)
# supported marker styles are: ".", ",", "o", "v", "^", "<", ">", "1", "2", "3", "4", "8", "s", "p", "P", "*", "h", "H", "+", "x", "X", "D", "d", "|", "_"
# supported line styles are '-', '--', '-.', ':', 'None', ' ', '', 'solid', 'dashed', 'dashdot', 'dotted'

ax.legend()

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_09.webp', bbox_inches='tight')

Logarithmic Axis

fig, ax = plt.subplots(1, 2, figsize=(12,8))

ax[0].plot(a,a,label="a, a")
ax[0].plot(a,(a**(3/2)+b**(1/2)),label="a,(a**(3/2)+b**(1/2)")
ax[0].grid(True)
ax[0].legend()
ax[0].set_title('Linear Scale')

ax[1].plot(a,a,label="a, a")
ax[1].plot(a,(a**(3/2)+b**(1/2)),label="a,(a**(3/2)+b**(1/2)")
ax[1].set_yscale('log')
ax[1].grid(True)
ax[1].legend()
ax[1].set_title('Log Scale')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_10.webp', bbox_inches='tight')

Polar Axis

np.random.seed(42)
N = 40
theta = np.linspace(0.0, 2*np.pi, N, endpoint=False)
radii = 10*np.random.rand(N)
width = np.pi/4*np.random.rand(N)
colours = plt.cm.winter(radii/10)

plt.figure(figsize=(10,10))
ax = plt.subplot(1,1,1, projection='polar')
ax.bar(
    theta,
    radii,
    width=width,
    bottom=0,
    color=colours,
    alpha=0.7
)
ax.set_title('Polar Bar Chart')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_27.webp', bbox_inches='tight')

radii2 = np.arange(0, 2, 0.01)
theta2 = 2*np.pi*radii2

plt.figure(figsize=(10,10))

ax = plt.subplot(111, projection='polar')
ax.plot(theta2, radii2, color='mediumspringgreen')
ax.set_rmax(2)
ax.set_rticks([0, 0.5, 1.5])
ax.set_title('Polar Line Chart')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_28.webp', bbox_inches='tight')

np.random.seed(42)
N = 200
radii3 = 3*np.random.rand(N)
theta3 = 2*np.pi*np.random.rand(N)
area = 50*2*np.pi*radii3**2
colours = theta3

fig = plt.figure(figsize=(10,10))

ax = fig.add_subplot(111, projection='polar')
plot = ax.scatter(theta3, radii3, c=colours, s=area, cmap='spring', alpha=0.8)

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_29.webp', bbox_inches='tight')

Twin Axes

fig, ax1 = plt.subplots(figsize=(12,8))

ax1.plot(a,(a**(3/2)+b**(1/2)), lw=2, color='dodgerblue')
ax1.set_ylabel(r"area $(m^2)$", fontsize=18, color='dodgerblue')
for label in ax1.get_yticklabels():
    label.set_color('dodgerblue')

ax2 = ax1.twinx()
ax2.plot(a,(a**(4/3)+b**(2/3)), lw=2, color='mediumorchid')
ax2.set_ylabel(r"volume $(m^3)$", fontsize=18, color='mediumorchid')
for label in ax2.get_yticklabels():
    label.set_color('mediumorchid')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_11.webp', bbox_inches='tight')

Annotation

fig, ax = plt.subplots(figsize=(12,8))
ax.set_title('Plot Annotation')
ax.plot(x**2+x, x**3)

plt.annotate(
    text='Wooh!',
    xy=(0, 0),
    xycoords='data',
    xytext=(0.3, 0.3),
    textcoords='axes fraction',
    va='top', ha='left',
    arrowprops=dict(facecolor='tomato', shrink=0),
    color='royalblue',
    weight='heavy'
)

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_12.webp', bbox_inches='tight')

Pie Plot

plt.pie(d)
plt.title('Pie Chart')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_13.webp', bbox_inches='tight')

d = [1, 2, 5, 7, 5, 7, 2]
e = (0., 0.05, 0.05, 0., 0., 0., 0.)
pie_labels = ['Cupim', 'Velit', 'Nulla', 'Leberkas', 'Cillum', 'Incididunt', 'Fugiat']

colors = plt.get_cmap('cool')(np.linspace(0.2, 0.7, len(d)))

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

wedges, texts, autotexts = ax.pie(
    d,
    autopct='%1.1f%%',
    pctdistance=0.6,
    colors=colors,
    labels = pie_labels,
    labeldistance=1.15,
    explode=e,
    startangle=130,
    wedgeprops={"linewidth": 1, "edgecolor": "white"},
    shadow=True
)

plt.setp(autotexts, size=13, color='white')
plt.setp(texts, size=14, color='darkslategray')
ax.set_title('Andouille Biltong Voluptate')

# ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
#        ylim=(0, 8), yticks=np.arange(1, 8))

fig.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_14.webp', bbox_inches='tight')

fig, ax = plt.subplots(figsize=(10,10))
size = 0.3

values = np.array([[88,44], [22,77], [99,11]])
value_sum = values.sum(axis=1)
value_flat = values.flatten()

value_sum_labels = ['Cupim', 'Velit', 'Nulla']
value_flat_labels = ['Leberkas', 'Cillum', 'Incididunt', 'Fugiat', 'Kielbasa', 'Picanha']

cmap = plt.get_cmap('cool')
outer_colors = cmap(np.linspace(0.1, 0.4, len(value_sum)))
inner_colors = cmap(np.linspace(0.5, 0.9, len(value_sum)))

wedges, texts, autotexts = ax.pie(
    value_sum,
    radius = 1,
    colors = outer_colors,
    labels = value_sum_labels,
    autopct='%1.1f%%',
    pctdistance=0.8,
    wedgeprops = {
        'linewidth': 1,
        'width': size,
        'edgecolor': "white"
    }
)

plt.setp(autotexts, size=13, color='white')
plt.setp(texts, size=14, color='darkslategray')

wedges2, texts2, autotexts2 = ax.pie(
    value_flat,
    radius = 1 - size,
    colors = inner_colors,
    labels = value_flat_labels,
    labeldistance=0.22,
    autopct='%1.1f%%',
    pctdistance=0.8,
    wedgeprops = {
        'linewidth': 1,
        'width': size,
        'edgecolor': "white"
    }
)

plt.setp(autotexts2, size=13, color='white')
plt.setp(texts2, size=10, color='darkslategray')

ax.set_title('Et Donut Burgdoggen Exercitatione')

fig.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_25.webp', bbox_inches='tight')

measurements = [
    '323 ppm Cupim',
    '72 ppm Velit',
    '112 ppm Nulla',
    '224 ppm Cillum',
    '56 ppm Incididunt'
]

results = [float(x.split(' ')[0]) for x in measurements]
substances = [str(x.split(' ')[-1]) for x in measurements]

def percentage(pct, values):
    absolute = int(pct/100. * np.sum(values))
    return '{:.1f}%\n({:d} ppm)'.format(pct, absolute)

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

wedges, texts, autotexts = ax.pie(
    result,
    autopct = lambda pct: percentage(pct, results)
)

ax.legend(
    wedges,
    substances,
    title = 'Measurement',
    bbox_to_anchor = (0.5, 0, 0.5, 1)
)

plt.setp(autotexts, size=13, color='white')
plt.setp(texts, size=14, color='darkslategray')

fig.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_26.webp', bbox_inches='tight')

Scatter Plot

plt.scatter(xz,yz)
plt.title('Scatter Plot')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_15.webp', bbox_inches='tight')

# size and color:
sizes = np.random.uniform(15, 80, len(xz))
colors = np.random.uniform(15, 80, len(xz))

fig, ax = plt.subplots()
ax.scatter(xz, yz, s=sizes, c=colors, vmin=0, vmax=100)
ax.set_title('Scatter Chart')
ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
       ylim=(0, 8), yticks=np.arange(1, 8))

fig.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_16.webp', bbox_inches='tight')

Bar Plot

plt.bar(a,b)
plt.title('Bar Chart')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_17.webp', bbox_inches='tight')

fig, ax = plt.subplots()

ax.bar(x, y, width=0.6, edgecolor="white", linewidth=0.7)
ax.set_title('Bar Chart')
ax.set(xlim=(0, 10), xticks=np.arange(1, 10),
       ylim=(0, 110))

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_18.webp', bbox_inches='tight')

Histogram

bins = np.linspace(0,20,20)

plt.hist(
    y_array[0],
    bins=bins,
    rwidth=0.8
)
plt.title('Histogram')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_19.webp', bbox_inches='tight')

fig, ax = plt.subplots()
ax.hist(xs, bins=8, linewidth=0.5, edgecolor="white")
ax.set_title('Histogram')
ax.set(xlim=(22, 33), xticks=np.arange(22, 33),
        ylim=(0, 20), yticks=np.linspace(0, 18, 9))

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_20.webp', bbox_inches='tight')

Box Plot

# generate two datasets - one with a standard deviation of 1 the other with std=2
data = [np.random.normal(0, std, 100) for std in range(1,3)]

plt.boxplot(data, vert=True, patch_artist=True)
plt.title('STD Boxplot')
plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_24.webp', bbox_inches='tight')

Fill Between Plot

fig, ax = plt.subplots()

ax.fill_between(x, y, y**(1/2), alpha=.5, linewidth=0)
ax.plot(x, (y + y**(1/2))/2, linewidth=2)
ax.set_title('Fill Between Chart')
ax.set(xlim=(-10, 10), xticks=np.arange(-10, 10),
        ylim=(0, 100))

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_21.webp', bbox_inches='tight')

Area under a Curve

from matplotlib.patches import Polygon

def f(x):
    return (x-3) * (x-4) * (x-7) + 77

a, b = 2, 9
x = np.linspace(0,10)
y = f(x)

fig, ax = plt.subplots(figsize=(12,8))

ax.plot(x, y, color='fuchsia', linewidth=2)
ax.set_title('Integral of the Area under the Curve')
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.spines['right'].set_visible(False)
ax.spines['top'].set_visible(False)

# select section of curve
ax.set_ylim(bottom=0)
ix = np.linspace(a,b)
iy = f(ix)
verts = [(a, 0), *zip(ix,iy), (b, 0)]
ax.set_xticks((a,b))
ax.set_xticklabels(('a','b'))
ax.set_yticks((f(a),f(b)))
ax.set_yticklabels(('f(a)','f(b)'))

# draw polygon under selection
poly = Polygon(verts, facecolor='dodgerblue', edgecolor='fuchsia')
ax.add_patch(poly)
# annotate
ax.text(
    0.5*(a+b), 30,
    r'$\int_a^b f(x)\mathrm{d}x$',
    color='white',
    fontsize='xx-large'
)

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_30.webp', bbox_inches='tight')

# i am not sure if `from matplotlib.patches import Polygon`
# has a method to calculate the area of a polygon?
# but it does work with `pip install shaply`:
from shapely.geometry import Polygon
polygon = Polygon(verts)
polygon.area
# 571.1428571428572

3D Projection Plot

np.random.seed(42)
n = 100
rng = np.random.default_rng()
xs = rng.uniform(23, 32, n)
ys = rng.uniform(0, 100, n)
zs = rng.uniform(-50, -25, n)

fig = plt.figure(figsize=(10,10))
ax = plt.axes(projection='3d')
ax.set_title('3D Line Chart')
ax.plot3D(xs, ys, zs)

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_22.webp', bbox_inches='tight')

fig, ax = plt.subplots(figsize=(12,8), subplot_kw={"projection": "3d"})

ax.scatter(xs, ys, zs)
ax.set_title('3D Scatterplot')
ax.set(xticklabels=[],
       yticklabels=[],
       zticklabels=[])

fig.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_23.webp', bbox_inches='tight')

Realtime Animation

from matplotlib.animation import FuncAnimation
from psutil import cpu_percent
from datetime import datetime

usage = []

cpu_use = cpu_percent()
usage.append((datetime.utcnow(), cpu_use))
usage
#[(datetime.datetime(2023, 5, 6, 8, 43, 39, 187158), 13.3),
#  (datetime.datetime(2023, 5, 6, 8, 43, 40, 67655), 12.2),
#  (datetime.datetime(2023, 5, 6, 8, 43, 40, 744222), 14.7)]

plt.plot(*zip(*usage), color='mediumspringgreen')
plt.title('CPU Usage in Percent')
plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_31.webp', bbox_inches='tight')

%matplotlib notebook
# only display 200 data points
frame_len = 200
data_points=[]

fig = plt.figure(figsize=(8,5))
fig.suptitle('Realtime CPU Usage [%]')

plt.ylim(1,100)
plt.tight_layout()

def animation(i):
    data_points.append((datetime.utcnow(), cpu_percent()))
    
    if len(y) <= frame_len:
        plt.cla()
        plt.plot(*zip(*data_points), color='mediumspringgreen', label='CPU Usage [%]')
    else:
        plt.cla()
        plt.plot(data_points[-frame_len:],color='mediumspringgreen', label='CPU Usage [%]')
        
anime = FuncAnimation(plt.gcf(), animation, interval=1000)

E = m*c²

from scipy import constants as sc

c_vac = sc.speed_of_light
mass = np.linspace(0,100)

def energy_conversion(mass):
    return mass * c_vac**2

energy = energy_conversion(mass)

fig = plt.figure(figsize=(8,5))
fig.suptitle('Mass to Energy Conversion')

plt.xlabel('Mass')
plt.ylabel('Energy')
plt.legend()
plt.plot(mass, energy, label='E = m*c²')

fig = plt.figure(figsize=(8,5))
fig.suptitle('Mass to Energy Conversion')

ax = fig.add_axes([0,0,1,1])

ax.plot(
    mass,energy,
    color='#fd18d9',
    linestyle='dashed',
    marker='h',
    markersize=8,
    markerfacecolor='lightseagreen',
    markeredgewidth=2,
    markeredgecolor='fuchsia',
    label="E = m*c²"
)

ax.legend(loc='upper left')
ax.set_xlabel('Mass')
ax.set_ylabel('Energy')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_33.webp', bbox_inches='tight')

fig, ax = plt.subplots(1, 2, figsize=(12,8))

ax[0].plot(
    mass,energy,
    color='lightseagreen',
    linestyle='dashed',
    label="E = m*c²"
)
ax[0].legend()
ax[0].set_xlabel('Mass')
ax[0].set_ylabel('Energy')
ax[0].grid(True)
ax[0].set_title('E = m*c²')

ax[1].plot(
    mass,energy,
    color='dodgerblue',
    linestyle='dashed',
    label="E = m*c²"
)
ax[1].set_yscale('log')
ax[1].grid(True)
ax[1].legend()
ax[1].set_xlabel('Mass')
ax[1].set_ylabel('Energy')
ax[1].set_title('E = m*c² (log)')

plt.savefig('assets/Matplotlib_Pyplot_Cheat_Sheet_34.webp', bbox_inches='tight')

mpolinowski/python-matplotlib-2023

Matplotlib Pyplot Cheat Sheet 2023

Functional API

Generate Data

Line Plot

Figure Object API

Line Plot

Subplots

Legend

Styling

Logarithmic Axis

Polar Axis

Twin Axes

Annotation

Pie Plot

Scatter Plot

Bar Plot

Histogram

Box Plot

Fill Between Plot

Area under a Curve

3D Projection Plot

Realtime Animation

E = m*c²