Python Matplotlib

Matplotlib

About Matplotlib

matplotlib

pip insall matplotlib

Matplotlib Line

import matplotlib.pyplot as plt

x = [ 3,  4,   5,  6 ]
y = [ 23, 42, 10, 19 ]
plt.plot(x, y)
plt.show()
#plt.savefig('line.png')

The numbers in the two lists are the values of the x and y axis respectively.

documentation of matplotlib.pyplot.plot

line

Line: y only

import matplotlib.pyplot as plt

y = [ 23, 42, 10, 19 ]
plt.plot(y)
plt.show()
#plt.savefig('plot-y.png')

The numbers in the lists are the values of the y axis.

The x axis defaults to the numbers 0, 1, 2, ... as is needed.

line

Line with labels (xlabel, ylabel)

import matplotlib.pyplot as plt

x = [ 3,  4,   5,  6 ]
y = [ 23, 42, 10, 19 ]

plt.plot(x, y)
plt.ylabel("height of things")
plt.xlabel("base values")

plt.show()
#plt.savefig('line_with_labels.png')

documentation of matplotlib.pyplot.plot

line with labels

Line with formatting

import matplotlib.pyplot as plt

x = [ 3,  4,   5,  6 ]
y = [ 23, 42, 10, 19 ]

#plt.plot(x, y, "b-")  # blue solid line
#plt.plot(x, y, "ro")  # red circles
#plt.plot(x, y, "gx")   # green x-es
plt.plot(x, y, "g--")   # green dashed line
plt.plot(x, y, "rD")   # red diamonds

#plt.show()
plt.savefig('line_with_formatting.png')

See the documentation of plot for a listing of styles.

line with labels

Matplotlib Line with dates

import datetime
import matplotlib.pyplot as plt

fig, subplots = plt.subplots()
subplots.plot(
    [datetime.date(2017, 1, 5), datetime.date(2017, 3, 5), datetime.date(2017, 5, 5)],
    [ 23, 17, 19 ],
    label='An example',
)
subplots.legend(loc='upper center', shadow=True)
fig.autofmt_xdate()
plt.show()
#plt.savefig('line_with_dates.png')

line with dates

Matplotlib Simple Pie

import matplotlib.pyplot as plt

wedge_sizes = [ 23, 42, 10, 19 ]

plt.pie(wedge_sizes)

plt.show()
#plt.savefig('simple_pie.png')

The number in the array represent the ratio of the areas. They do NOT have to add up to a 100.

documentation of matplotlib.pyplot.pie

simple pie diagram

Matplotlib Simple Pie with params

import matplotlib.pyplot as plt

plt.pie(
    x = [ 23, 42, 10, 19 ],
    explode = [0, 0, 0.1, 0.3],
    labels = ["failure", "success", "maybe", "what?"],
    colors = ["red",  "green",  "blue", "#A395C1"],
    shadow = True,
    radius = 1.1,
)

#plt.show()
plt.savefig('simple_pie_params.png')

Simple pie diagram with parameters

pyplot pie

Matplotlib Pie

import matplotlib.pyplot as plt


# Make a square figure and axes
plt.figure(1, figsize=(6, 6))
#ax = plt.axes([0.1, 0.1, 0.8, 0.8])

labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
fracs = [15, 30, 45, 10]

explode = (0, 0.05, 0, 0)
plt.pie(fracs,
    explode=explode,
    labels=labels,
    autopct='%1.1f%%',
    shadow=True)
plt.title('Raining Hogs and Dogs',
    bbox={'facecolor': '0.8', 'pad': 5})

plt.show()
#plt.savefig('pie.png')
#plt.savefig('pie.pdf')

Matplotlib Pie (test cases)

import matplotlib.pyplot as plt

cases = {
    'success': 38,
    'failure': 7,
    'skipped': 3,
    'xfailed': 8,
    'xpassed': 4,
}

explode = (0, 0.1, 0.1, 0.1, 0.1)
labels = cases.keys()
sizes = cases.values()

fig1, ax1 = plt.subplots()
ax1.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%', shadow=True, startangle=90)
ax1.axis('equal')

plt.tight_layout()
#plt.show()
plt.savefig('pie_for_tests.png')

Bar

import matplotlib.pyplot as plt

x = [0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5]
y = [4.8, 5.9, 2.5, 4.6, 6.5, 6.6, 2.6, 3.0]

fig, ax = plt.subplots()

ax.bar(x, y, width=1, edgecolor="white", linewidth=0.7)
ax.set(xlim=(0, 8), xticks=range(1, 8),
       ylim=(0, 8), yticks=range(1, 8))

#plt.show()
plt.savefig('bars.png')

bars

Histogram

histogram (to group the values into bins)

import matplotlib.pyplot as plt
import numpy as np

np.random.seed(1)
x = 4 + np.random.normal(0, 1.5, 200)

# plot:
fig, ax = plt.subplots()

ax.hist(x, bins=8, linewidth=0.5, edgecolor="white")

ax.set(xlim=(0, 8), xticks=range(1, 8),
       ylim=(0, 56), yticks=np.linspace(0, 56, 9))

#plt.show()
plt.savefig('histogram.png')

Histogram

Fill between

import matplotlib.pyplot as plt
import numpy as np

# make data
np.random.seed(1)
x = np.linspace(0, 8, 16)
y1 = 3 + 4*x/8 + np.random.uniform(0.0, 0.5, len(x))
y2 = 1 + 2*x/8 + np.random.uniform(0.0, 0.5, len(x))

# plot
fig, ax = plt.subplots()

ax.fill_between(x, y1, y2, alpha=.5, linewidth=0)
ax.plot(x, (y1 + y2)/2, linewidth=2)

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

#plt.show()
plt.savefig('fill_between.png')

Fill between

3D bars

import matplotlib.pyplot as plt
import numpy as np

x = [1, 1, 2, 2]
y = [1, 2, 1, 2]
z = [0, 0, 0, 0]
dx = np.ones_like(x)*0.5
dy = np.ones_like(x)*0.5
dz = [2, 3, 1, 4]

# Plot
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
ax.bar3d(x, y, z, dx, dy, dz)

ax.set(xticklabels=[],
       yticklabels=[],
       zticklabels=[])

#plt.show()
plt.savefig('3dbars.png')

Fill between

Scatter, histogram

scatter - just the values
plt.hist(data, bin=10)

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Python Matplotlib